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Cancers
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Metastatic Colorectal Cancer
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Metastatic Colorectal Cancer

A special issue of Cancers (ISSN 2072-6694).

Deadline for manuscript submissions: closed (31 July 2020) | Viewed by 54369

Special Issue Editors

Dr. Paola Ulivi

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Guest Editor
Biosciences Laboratory, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, via P. Maroncelli 40, 47014 Meldola, Italy
Interests: translational research; biomarkers; liquid biopsy; oncology
Special Issues, Collections and Topics in MDPI journals
Dr. Alessandro Passardi

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Guest Editor
Department of Medical Oncology, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014 Meldola, Italy
Interests: colorectal cancer; gastrointestinal tumors; translational research; immunotherapy
Special Issues, Collections and Topics in MDPI journals
Dr. Giorgia Marisi

E-Mail Website
Guest Editor
Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori “Dino Amadori” (IRST), via P. Maroncelli 40, 47014 Meldola, Italy
Interests: molecular biology; oncology; translational research; liquid biopsy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Colorectal cancer (CRC) is the third most commonly diagnosed cancer in males and the second in females. Translational research has led to significant benefits in the management of patients with metastatic disease, and precision medicine is becoming the goal of scientific research.

The introduction of molecular targeted or antiangiogenic agents have significantly improved patient outcomes, but predictive markers of efficacy are not completely understood. Furthermore, immune checkpoint inhibitors have recently made their way broadly into clinical practice.

A new approach for biomarker detection is the use of liquid biopsy, which has the potential to replace tumor tissue analysis in clinical practice, and can enable the monitoring of tumor burden and the detection of tumor heterogeneity and molecular resistance to therapy.

Dr. Paola Ulivi
Dr. Alessandro Passardi
Dr. Giorgia Marisi
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

  • immunotherapy
  • targeted therapy
  • biomarkers
  • angiogenesis
  • EGFR pathways
  • circulating tumor cells
  • tumor heterogeneity
  • liquid biopsy
  • clinical trials
  • molecular pathology

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Published Papers (15 papers)

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Editorial

Jump to: Research, Review

3 pages, 183 KiB  
Editorial
Metastatic Colorectal Cancer
by Alessandro Passardi, Giorgia Marisi and Paola Ulivi
Cancers 2021, 13(24), 6346; https://doi.org/10.3390/cancers13246346 - 17 Dec 2021
Cited by 1 | Viewed by 2141
Abstract
International experts in the study of metastatic colorectal cancer (mCRC) present this series of 14 articles (eleven original articles and three literature reviews) [...] Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)

Research

Jump to: Editorial, Review

20 pages, 1835 KiB  
Article
Landscape of Genome-Wide DNA Methylation of Colorectal Cancer Metastasis
by Carmen Ili, Kurt Buchegger, Hannah Demond, Juan Castillo-Fernandez, Gavin Kelsey, Louise Zanella, Michel Abanto, Ismael Riquelme, Jaime López, Tamara Viscarra, Patricia García, Enrique Bellolio, David Saavedra and Priscilla Brebi
Cancers 2020, 12(9), 2710; https://doi.org/10.3390/cancers12092710 - 22 Sep 2020
Cited by 21 | Viewed by 5903
Abstract
Colorectal cancer is a heterogeneous disease caused by both genetic and epigenetics factors. Analysing DNA methylation changes occurring during colorectal cancer progression and metastasis formation is crucial for the identification of novel epigenetic markers of patient prognosis. Genome-wide methylation sequencing of paired samples [...] Read more.
Colorectal cancer is a heterogeneous disease caused by both genetic and epigenetics factors. Analysing DNA methylation changes occurring during colorectal cancer progression and metastasis formation is crucial for the identification of novel epigenetic markers of patient prognosis. Genome-wide methylation sequencing of paired samples of colon (normal adjacent, primary tumour and lymph node metastasis) showed global hypomethylation and CpG island (CGI) hypermethylation of primary tumours compared to normal. In metastasis we observed high global and non-CGI regions methylation, but lower CGI methylation, compared to primary tumours. Gene ontology analysis showed shared biological processes between hypermethylated CGIs in metastasis and primary tumours. After complementary analysis with The Cancer Genome Atlas (TCGA) cohort, FIGN, HTRA3, BDNF, HCN4 and STAC2 genes were found associated with poor survival. We mapped the methylation landscape of colon normal tissues, primary tumours and lymph node metastasis, being capable of identified methylation changes throughout the genome. Furthermore, we found five genes with potential for methylation biomarkers of poor prognosis in colorectal cancer patients. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
►▼ Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Methylation patterns of non-CGI regions in normal colon tissue (NAT), primary tumour and lymph node metastasis (LNM) samples of three CRC patients. (<b>A</b>) Mean methylation of non-CGI regions for each individual patient. The black line indicates the mean of the three patients (one-way ANOVA, <span class="html-italic">p =</span> 0.1360). (<b>B</b>) Scatterplot comparing methylation levels between NAT and primary tumour samples and (<b>C</b>) between NAT and LMN samples. Each dot indicates the average methylation of a 200 CpG window (excluding CGIs). (<b>D</b>) Principal component analysis showing clustering of normal, primary tumour and LNM samples on PC1 and PC4. (<b>E</b>) Screenshot of the genome showing large regions with lower methylation levels in primary tumour samples compared to NAT and LMN samples. Each bar represents a 200 CpG window. The height and colour of the bar indicate the methylation values. NAT: normal adjacent tissue; LNM: lymph node metastasis.</p> Full article ">Figure 2
<p>CGI methylation levels in normal adjacent tissue, primary tumour and lymph node metastasis samples of CRC patients. (<b>A</b>) Beanplots showing DNA methylation levels of lowly (&lt;40%) and highly (&gt;80%) methylated CGIs (<span class="html-italic">n</span> = 9776). (<b>B</b>) Bar chart showing the proportion in which different CGI features are represented in all analysed CGIs (<span class="html-italic">n</span> = 7009) and in differentially methylated CGIs (<span class="html-italic">n</span> = 246). (<b>C</b>) Scatterplot comparing DNA methylation levels of CGIs between NAT and primary tumour samples and (<b>D</b>) between NAT and LMN samples in which each dot represents a CGI (<span class="html-italic">n</span> = 7009). Differentially methylated CGIs are highlighted in blue. (<b>E</b>) Heatmap showing methylation levels of 246 differentially methylated CGIs for each individual patient. Each bar represents a CGI and the colour scale indicates its methylation level. (<b>F</b>) Strip chart comparing methylation percentage of 204 CGIs in NAT, primary tumour and LNM samples (1.5 kb upstream to coding-genes) (*** <span class="html-italic">p</span> &lt; 0.001, Kruskal–Wallis followed by Dunn’s test). NAT: normal adjacent tissue; LNM: lymph node metastasis.</p> Full article ">Figure 3
<p>Gene ontology analysis comparing hypermethylated CGIs between NAT, primary tumour and LNM. (<b>A</b>) The circus plot shows how genes from the input gene lists overlap genes with differentially methylated CGIs enriched for ontology terms of primary tumour and NAT. On the outside, each arc represents the identity of each gene list. On the inside, each arc represents a gene list, where each gene has a spot on the arc. Dark orange colour represents the genes that appear in multiple lists and light orange colour represents genes that are unique to that gene list. Purple lines link the same genes that are shared by multiple gene lists. (<b>B</b>) Circus plot showing the shared term level, where blue curves link genes that belong to the same enriched ontology term, between primary and NAT. The inner circle represents gene lists, where hits are arranged along the arc. Genes that hit multiple lists are coloured in dark orange, and genes unique to a list are shown in light orange. (<b>C</b>) Dendrogram showing enriched ontology clusters across primary tumour and NAT. The colour scale of the heatmap cells represents their <span class="html-italic">p</span>-values, white cells indicate the lack of enrichment for that term in the corresponding gene list. (<b>D</b>) The circus plot shows how genes from the input gene lists overlap genes with differentially methylated CGIs enriched for ontology terms (42 genes) of primary tumour and LNM. (<b>E</b>) Circus plot showing the shared term level, where blue curves link genes that belong to the same enriched ontology term between primary tumour and LNM. (<b>F</b>) Dendrogram showing enriched ontology clusters across input gene lists, between primary tumour and LNM. (<b>G</b>) Line chart showing the differentially methylated CGIs across the colon tissues (NAT, primary tumour and LNM). (<b>H</b>) Heatmap representing the methylation percentage of 42 CGIs in NAT, primary tumour and LNM. (NAT: normal adjacent tissue; PT: primary tumour; LNM: lymph node metastasis).</p> Full article ">Figure 4
<p>Kaplan–Meier survival curves for patients with colorectal cancer from The Cancer Genome Atlas (TCGA) cohort. The solid lines indicate patients with low levels of CGI methylation and the dotted lines indicate patients with hypermethylation of CGIs overlapping candidate genes. (<b>A</b>) <span class="html-italic">FIGN</span> (<span class="html-italic">p =</span> 0.030); (<b>B</b>) <span class="html-italic">HTRA3</span> (<span class="html-italic">p =</span> 0.009); (<b>C</b>) <span class="html-italic">BDNF</span> (<span class="html-italic">p =</span> 0.002); (<b>D</b>) <span class="html-italic">HCN4</span> (<span class="html-italic">p =</span> 0.016) and (<b>E</b>) <span class="html-italic">STAC2</span> (<span class="html-italic">p =</span> 0.007). Stratified log-rank test.</p> Full article ">
35 pages, 31412 KiB  
Article
Isolation and Characterization of Two Novel Colorectal Cancer Cell Lines, Containing a Subpopulation with Potential Stem-Like Properties: Treatment Options by MYC/NMYC Inhibition
by Jan Schulte am Esch, Beatrice Ariane Windmöller, Johannes Hanewinkel, Jonathan Storm, Christine Förster, Ludwig Wilkens, Martin Krüger, Barbara Kaltschmidt and Christian Kaltschmidt
Cancers 2020, 12(9), 2582; https://doi.org/10.3390/cancers12092582 - 10 Sep 2020
Cited by 11 | Viewed by 4784
Abstract
Cancer stem cells (CSC) are crucial mediators of cancer relapse. Here, we isolated two primary human colorectal cancer cell lines derived from a rectal neuroendocrine carcinoma (BKZ-2) and a colorectal adenocarcinoma (BKZ-3), both containing subpopulations with potential stem-like properties. Protein expression of CSC-markers [...] Read more.
Cancer stem cells (CSC) are crucial mediators of cancer relapse. Here, we isolated two primary human colorectal cancer cell lines derived from a rectal neuroendocrine carcinoma (BKZ-2) and a colorectal adenocarcinoma (BKZ-3), both containing subpopulations with potential stem-like properties. Protein expression of CSC-markers prominin-1 and CD44 antigen was significantly higher for BKZ-2 and BKZ-3 in comparison to well-established colon carcinoma cell lines. High sphere-formation capacity further confirmed the existence of a subpopulation with potential stem-like phenotype. Epithelial–mesenchymal transition markers as well as immune checkpoint ligands were expressed more pronounced in BKZ-2. Both cell populations demonstrated N-myc proto-oncogene (NMYC) copy number gain. Myc proto-oncogene (MYC)/NMYC activity inhibitor all-trans retinoic acid (ATRA) significantly reduced the number of tumor spheres for both and the volume of BKZ-2 spheres. In contrast, the sphere volume of ATRA-treated BKZ-3 was increased, and only BKZ-2 cell proliferation was reduced in monolayer culture. Treatment with KJ-Pyr-9, a specific inhibitor of MYC/NMYC-myc-associated factor X interaction, decreased survival by the induction of apoptosis of both. In summary, here, we present the novel colorectal cancer cell lines BKZ-2 and BKZ-3 as promising cellular in vitro models for colorectal carcinomas and identify the MYC/NMYC molecular pathway involved in CSC-induced carcinogenesis with relevant therapeutic potential. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
►▼ Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Clinical imaging derived from the two donors of the colorectal cancer cell lines. Patient BKZ-2: (<b>A</b>) Computerized tomography (CT)-scan with demonstration of a rectal stenotic mass (orange arrows) with pre-stenotic obstructed bowel (yellow double arrow). Endoscopic appearance of carcinoma BKZ-2 (<b>B</b>) with intestinal discharge following (<b>C</b>) endoscopic bowel stenting of the neoplastic stenosis. (<b>D</b>) Staging CT-scan visualizing hepatic metastases (orange arrows). Patient BKZ-3: (<b>E</b>) CT-scan indicating the neoplastic mass of the left colon (orange arrows) with pre-stenotic obstructed bowel (yellow double arrows).</p> Full article ">Figure 2
<p>Immunohistochemical characterization of the primary rectal large cell neuroendocrine carcinoma (NEC) and the colorectal adenocarcinoma (AC). NEC tissue was tested positive for (<b>A</b>) Synaptophysin, (<b>B</b>) neural cell adhesion molecule (CD56), (<b>C</b>) epithelial marker pan-cytokeratin (panCK) and (<b>D</b>) special AT-rich sequence-binding protein 2 (SATB2), but was negative for (<b>E</b>) cytokeratin 20 (CK20) and (<b>F</b>) cytokeratin 7 (CK7). Moreover, immunohistological staining for (<b>G</b>) the intestinal differentiation marker homeobox protein CDX2 was negative. (<b>H</b>) Staining for the proliferation marker protein Ki-67 (KI67) revealed 25% positive cells. Further immunohistochemical stainings of the NEC tissue displayed positivity for the (<b>I</b>/<b>J</b>) myc proto-oncogene protein (MYC) and (<b>K</b>/<b>L</b>) N-myc proto-oncogene protein (NMYC). (<b>M</b>) Immunohistochemical staining for programed death ligand 1 (PDL1) revealed only slight expression with 2% of vital tumor cells being positive. AC tissue was tested negative for neuroendocrine marker (<b>N</b>) Synaptophysin and (<b>O</b>) CK7, but was positive for (<b>P</b>) CK20 and (<b>Q</b>) SATB2. AC revealed (<b>R</b>) 50% KI67 highly positive cells and 25% cells with moderate KI67 expression. (<b>S</b>) Immunohistochemical characterization of PDL1 expression displayed 0% positive vital tumor cells, but revealed positivity for both (<b>T</b>/<b>U</b>) MYC and (<b>V</b>/<b>W</b>) NMYC in the AC tissue.</p> Full article ">Figure 3
<p>Successful isolation of the rectal large cell neuroendocrine carcinoma (NEC)-derived cancer cell line BKZ-2 and the colorectal adenocarcinoma (AC)-derived cancer cell line BKZ-3. (<b>A</b>) For the isolation of those cell lines that contain a subpopulation of cells with potential stem-like properties a tissue sample of either the (<b>B</b>) rectal large cell NEC or the (<b>C</b>) colorectal AC was obtained, mechanically and enzymatically disintegrated, and cultivated in CSC medium supplemented with fetal calf serum (FCS), leading to (<b>D</b>/<b>E</b>) adherent growing cells. (<b>F</b>/<b>H</b>) Cultivation of the cells with the addition of heparin and in the absence of FCS led to the formation of spheres, further validating stem-like properties of BKZ-2 and BKZ-3. (<b>G</b>/<b>I</b>) Quantification of the averaged sphere diameter showed a significant increase after the addition of heparin in comparison to the control for BKZ-2 and BKZ-3, regardless of the tested heparin concentrations. Moreover, BKZ-2 showed a continuous growth of the spheres over a time-period of one week. Non-parametric Kruskal-Wallis test (<span class="html-italic">p</span> ≤ 0.05), followed by Dunn’s Multiple Comparison post-hoc test. <span class="html-italic">n</span> = 5, *** <span class="html-italic">p</span> ≤ 0.001, ** <span class="html-italic">p</span> ≤ 0.01. Mean ± standard error of the mean (SEM). n.d. = not detectable.</p> Full article ">Figure 4
<p>BKZ-2 and BKZ-3 reveal higher population doubling times and formed higher numbers of spheres in comparison to HT-29 and HCT-116. (<b>A</b>) Quantification of the population doubling times of the newly isolated colorectal cancer cell lines BKZ-2 and BKZ-3 as well as the common colon adenocarcinoma cell line HT-29 and colon carcinoma cell line HCT-116 revealed a significantly higher population doubling time for BKZ-2 in comparison to BKZ-3, HT-29 and HCT-116. Moreover, BKZ-3 and HT-29 displayed a significantly higher population doubling time when compared with HCT-116. (<b>B</b>–<b>E</b>) All cell populations formed spheres when 5000 cells per 200 μL cancer stem cell (CSC) medium containing 4 μg/mL heparin were cultured in low adhesion 96 well-plates. Quantification of the (<b>F</b>) volume of spheres formed by each cell line showed a significantly higher volume for HT-29 and HCT-116 when compared to BKZ-2 and BKZ-3. Moreover, sphere volume of HT-29 was significantly higher in comparison to HCT-116. Further quantification concerning (<b>G</b>) the number of formed spheres in relation to seeded cells revealed significantly less percent spheres for HT-29 and HCT-116 in comparison to BKZ-2 and BKZ-3. Non-parametric Mann-Whitney-test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">n</span> ≤ 3, *** <span class="html-italic">p</span> ≤ 0.001, ** <span class="html-italic">p</span> ≤ 0.01, * <span class="html-italic">p</span> ≤ 0.05. Mean ± SEM (standard error of the mean).</p> Full article ">Figure 5
<p>BKZ-2 and BKZ-3 express higher amounts of prominin-1 (CD133) and CD44 antigen (CD44) in comparison to HT-29 and HCT-116. Immunocytochemical analysis of BKZ-2 and BKZ-3 displayed high positivity for the cancer stem cell (CSC)-markers (<b>A/C</b>) CD133, CD44 and (<b>B/D</b>) Nestin, validating the isolation of two new cell lines that contain a subpopulation of cells with potential stem-like properties. Immunocytochemical analysis of the common colon carcinoma cell lines HT-29 and HCT-116 only displayed slight expression of the CSC-markers (<b>E</b>/<b>G</b>) CD133, CD44 and (<b>F</b>/<b>H</b>) Nestin. Quantification of the percentage of (<b>I</b>) CD133 high, medium and low cells revealed a significantly elevated amount of CD133 high BKZ-3 cells in comparison to BKZ-2, HT-29 and HCT-116. Moreover, the percentage of HT-29 and HCT-116 CD133 low cells was significantly higher when compared to BKZ-2 and BKZ-3. Quantification of (<b>J</b>) CD44 high, medium and low cells displayed for both populations a significantly higher percentage of CD44 high cells in comparison to HT-29 and HCT-116. Non-parametric Kruskal-Wallis equality-of-populations rank test (<span class="html-italic">p</span> ≤ 0.05) followed by Mann-Whitney test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">n</span> = 3, ** <span class="html-italic">p</span> ≤ 0.01, * <span class="html-italic">p</span> ≤ 0.05, ns = not significant. Mean ± SEM (standard error of the mean).</p> Full article ">Figure 6
<p>BKZ-2 and BKZ-3 both show aldehyde dehydrogenase (ALDH) activity. Flow-cytometric-analysis of ALDH activity of (<b>B</b>) BKZ-2 and (<b>D</b>) BKZ-3 revealed 7.993% ALDH high cells for BKZ-2 and 26.141% ALDH high cells for BKZ-3 in comparison to the appropriate (<b>A</b>/<b>C</b>) control with the specific ALDH inhibitor diethylaminobenzaldehyde (DEAB).</p> Full article ">Figure 7
<p>BKZ-2 and BKZ-3 show higher messenger ribonucleic acid (mRNA)-level of cancer stem cell (CSC)- and epithelial-mesenchymal-transition (EMT)-markers as well as immune checkpoint ligands in comparison to human dermal fibroblasts (HDF). Quantitative polymerase chain reaction revealed an expression of CSC-markers (<b>A</b>) prominin-1 (<span class="html-italic">CD133</span>), (<b>B</b>) CD44 antigen (<span class="html-italic">CD44</span>), (<b>C</b>) leucine rich repeat containing G protein-coupled receptor 5 <span class="html-italic">(LGR5</span>), (<b>D</b>) epithelial cell adhesion molecule (<span class="html-italic">EPCAM</span>), (<b>E</b>) SRY-box transcription factor 2 (<span class="html-italic">SOX2</span>) and (<b>F</b>) octamer-binding transcription factor 4 (<span class="html-italic">OCT4</span>) in both cell lines. Comparison of the two cell lines, demonstrated significant differences of the relative mRNA expression for <span class="html-italic">CD133</span>, <span class="html-italic">CD44</span>, <span class="html-italic">LGR5</span> and <span class="html-italic">SOX2</span>. Further analysis revealed an expression of the key transcription factors of the process of EMT (<b>G</b>) twist family bHLH transcription factor 1 (<span class="html-italic">TWIST</span>), (<b>H</b>) snail family transcriptional repressor 2 (<span class="html-italic">SLUG</span>) and (<b>I</b>) snail family transcriptional repressor 1 (<span class="html-italic">SNAIL</span>), with <span class="html-italic">TWIST</span> and <span class="html-italic">SLUG</span> being significantly different expressed in BKZ-2 and BKZ-3. Moreover, quantification displayed a significantly altered expression of the immune checkpoint ligands (<b>J</b>) programmed death ligand 1 (<span class="html-italic">PDL1</span>) and (<b>K</b>) programmed death ligand 2 (<span class="html-italic">PDL2</span>) in the two cell lines. Non-parametric Mann-Whitney-test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> ≤ 0.05. Mean ± SEM (standard error of the mean).</p> Full article ">Figure 8
<p>BKZ-2 cells reveal higher levels of Synaptophysin (SYP) and snail family transcriptional repressor 2 (SLUG) protein in comparison to BKZ-3 cells. Immunocytochemical stainings revealed the expression of neuroendocrine and cancer stem cell marker (<b>A/C</b>) Synaptophysin as well as the expression of (<b>B/D</b>) SLUG, one of the key transcription factors of the process of epithelial to mesenchymal transition in both populations. (<b>E</b>) Quantification of cells positive for nuclear Synaptophysin revealed a mean of 90.27% for BKZ-2 and 92.92% for BKZ-3. (<b>G</b>) Further classification in Synaptophysin high and low cells, showed a significantly higher amount of Synaptophysin low nuclei in comparison to Synaptophysin high nuclei for both BKZ-2 and BKZ-3. However, BKZ-2 revealed a significantly higher percentage of Synaptophysin high nuclei in comparison to BKZ-3. (<b>F</b>) Quantification of nuclear positivity for SLUG displayed 100% positive cells for BKZ-2 and a mean of 92.57% positive cells for BKZ-3. (<b>H</b>) Comparison of SLUG high and low cells displayed a significantly higher amount of SLUG high cells of BKZ-2 when compared to BKZ-3. Moreover, BKZ-3 cells in general showed a significantly higher percentage of SLUG low cells in comparison to the amount of SLUG high cells. Non-parametric Mann-Whitney-test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">n</span> = 3, ** <span class="html-italic">p</span> ≤ 0.01, * <span class="html-italic">p</span> ≤ 0.05, ns = not significant. Mean ± SEM (standard error of the mean).</p> Full article ">Figure 9
<p>All-trans retinoic acid (ATRA) reduce number of BKZ-2 and BKZ-3 formed spheres respectively, but cause opposed effects concerning sphere volume of BKZ-2 and BKZ-3. Cells were cultured in an amount of 5000 cells per 200 μL cancer stem cell (CSC) medium containing 4 μg/mL heparin in a low adhesion 96 well-plate. Medium was supplemented with (<b>A</b>/<b>G</b>) dimethylsulfoxide, (<b>B</b>/<b>H</b>) 1 μM ATRA, (<b>C</b>/<b>I</b>) 5 μM ATRA or (<b>D</b>/<b>J</b>) 10 μM ATRA. (<b>A</b>–<b>D</b>) Representative images already display a morphological change of BKZ-2 after the cultivation with 1 μM ATRA, indicated by the adherence of the cells (arrows). Quantification of the (<b>E</b>) volume of spheres formed by BKZ-2 cells showed a significant decrease after ATRA-treatment. Further quantification concerning (<b>F</b>) the number of spheres revealed a tendency for fewer spheres after ATRA-treatment for BKZ-2. (<b>G</b>–<b>J</b>) Representative images of BKZ-3 spheres and quantification of the (<b>K</b>) volume of spheres formed by BKZ-3 cells showed a significant increase subsequent to treatment with 10 μM ATRA. Further quantification concerning the (<b>L</b>) number of spheres revealed a significant decrease of the number of spheres after the treatment with 10 μM ATRA. Non-parametric Mann-Whitney-test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">n</span> = 3, *** <span class="html-italic">p</span> ≤ 0.001, ** <span class="html-italic">p</span> ≤ 0.01, * <span class="html-italic">p</span> ≤ 0.05. Mean ± SEM (standard error of the mean).</p> Full article ">Figure 10
<p>All-trans retinoic acid (ATRA)-treatment reduced total cell mass of BKZ-2 formed spheres, but does not have an effect on total cell mass of BKZ-3 formed spheres. Analysis of the quantification of the (<b>A</b>) volume of the spheres formed by the two colorectal cancer cell lines revealed a significant difference after ATRA-treatment. ATRA-treatment led to the formation of significant bigger spheres formed by BKZ-3 in comparison to BKZ-2. Further quantification of (<b>B</b>) the total cell mass revealed a significantly decreased cell mass for BKZ-2 upon ATRA stimulation, while the total cell mass of BKZ-3 was not altered. Non-parametric Mann-Whitney-test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> ≤ 0.05, ns = not significant. Mean ± SEM (standard error of the mean).</p> Full article ">Figure 11
<p>Inhibition of the myc proto-oncogene protein (MYC) and N-myc proto-oncogene protein (NMYC) significantly decreases the survival rate of BKZ-2 and BKZ-3 cells. Immunocytochemical staining revealed a strong expression of the oncogene (<b>A</b>/<b>B</b>) NMYC, as well as a nuclear expression of the oncogene (<b>C</b>/<b>D</b>) MYC, in both BKZ-2 and BKZ-3 on protein level. Evaluation of the haploid copy number of the two oncogenes, demonstrated a two-fold increase of the haploid copy number of (<b>E</b>) <span class="html-italic">NMYC</span>, but a normal haploid copy number for (<b>F</b>) <span class="html-italic">MYC</span> within both cell lines. To investigate the influence of the MYC/NMYC inhibitor KJ-Pyr-9 on the proliferation, 3000 cells per 100 μL cancer stem cell medium were cultured in a 96 well for 120 h with the inhibitor or dimethylsulfoxide and 10% fetal calf serum. Afterwards, metabolism was measured using Orangu<sup>TM</sup> (Cell Guidance Systems, Cambridge, UK) and cell count was determined by using a standard curve. (<b>G</b>) Normalized survival rate was quantified and significantly decreased after exposure to values greater than 20 μM of KJ-Pyr-9 in comparison to the control for BKZ-2 and BKZ-3. Further comparisons between the two cell lines displayed a significant decrease of the survival rate of BKZ-2 in comparison to BKZ-3 for all inhibitor concentrations. (<b>H</b>) Although comparison of survival rates after KJ-Pyr-9-treatment showed significantly higher survival of HCT-116 when compared to BKZ-2 after 20 μM K-Pyr-9, cell survival of BKZ-2 and BKZ-3 was significantly improved in comparison to HT-29 and HCT-116 after treatment with inhibitor concentrations over 40 μM. Non-parametric Mann-Whitney-test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> ≤ 0.05. Mean ± SEM (standard error of the mean).</p> Full article ">Figure 12
<p>Myc proto-oncogene (MYC)/N-myc proto-oncogene (NMYC) inhibitor KJ-Pyr-9 induces apoptosis of BKZ-2 and BKZ-3. Representative images of immunocytochemical staining for cleaved caspase 3 (CASP3) after KJ-Pyr-9-treatment of (<b>A</b>–<b>E</b>) BKZ-2 and (<b>F</b>–<b>J</b>) BKZ-3. (<b>K</b>) Quantification of the percentage of cleaved CASP3 positive cells after the addition of 10 μM KJ-Pyr-9 revealed a significantly higher amount for BKZ-2 with about 94% in comparison to BKZ-3 with about 4%. However, concentrations higher than 40 μM lead to 100% cleaved CASP3 positive cells for BKZ-2 and BKZ-3. Student’s <span class="html-italic">t</span>-test (<span class="html-italic">p</span> ≤ 0.05). <span class="html-italic">n</span> = 3, *** <span class="html-italic">p</span> ≤ 0.001. Mean ± SEM (standard error of the mean).</p> Full article ">
18 pages, 1631 KiB  
Article
The Level of Preoperative Plasma KRAS Mutations and CEA Predict Survival of Patients Undergoing Surgery for Colorectal Cancer Liver Metastases
by Jiri Polivka, Jindra Windrichova, Martin Pesta, Katerina Houfkova, Hana Rezackova, Tereza Macanova, Ondrej Vycital, Radek Kucera, David Slouka and Ondrej Topolcan
Cancers 2020, 12(9), 2434; https://doi.org/10.3390/cancers12092434 - 27 Aug 2020
Cited by 22 | Viewed by 3073
Abstract
Colorectal cancer (CRC) belongs to the most common cancers. The liver is a predominant site of CRC dissemination. Novel biomarkers for predicting the survival of CRC patients with liver metastases (CLM) undergoing metastasectomy are needed. We examined KRAS mutated circulating cell-free tumor DNA [...] Read more.
Colorectal cancer (CRC) belongs to the most common cancers. The liver is a predominant site of CRC dissemination. Novel biomarkers for predicting the survival of CRC patients with liver metastases (CLM) undergoing metastasectomy are needed. We examined KRAS mutated circulating cell-free tumor DNA (ctDNA) in CLM patients as a prognostic biomarker, independently or in combination with carcinoembryonic antigen (CEA). Thereby, a total of 71 CLM were retrospectively analyzed. Seven KRAS G12/G13 mutations was analyzed by a ddPCR™ KRAS G12/G13 Screening Kit on QX200 Droplet Digital PCR System (Bio-Rad Laboratories, Hercules, CA, USA) in liver metastasis tissue and preoperative and postoperative plasma samples. CEA were determined by an ACCESS CEA assay with the UniCel DxI 800 Instrument (Beckman Coulter, Brea, CA, USA). Tissue KRAS positive liver metastases was detected in 33 of 69 patients (47.8%). Preoperative plasma samples were available in 30 patients and 11 (36.7%) were KRAS positive. The agreement between plasma- and tissue-based KRAS mutation status was 75.9% (22 in 29; kappa 0.529). Patients with high compared to low levels of preoperative plasma KRAS fractional abundance (cut-off 3.33%) experienced shorter overall survival (OS 647 vs. 1392 days, p = 0.003). The combination of high preoperative KRAS fractional abundance and high CEA (cut-off 3.33% and 4.9 µg/L, resp.) best predicted shorter OS (HR 13.638, 95%CI 1.567–118.725) in multivariate analysis also (OS HR 44.877, 95%CI 1.59–1266.479; covariates: extend of liver resection, biological treatment). KRAS mutations are detectable and quantifiable in preoperative plasma cell-free DNA, incompletely overlapping with tissue biopsy. KRAS mutated ctDNA is a prognostic factor for CLM patients undergoing liver metastasectomy. The best prognostic value can be reached by a combination of ctDNA and tumor marker CEA. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>Significant changes in KRAS fractional abundance between pre- and post-operative plasma samples in patients undergoing surgery for colorectal cancer liver metastases (<span class="html-italic">p</span> = 0.043).</p> Full article ">Figure 2
<p>Significant changes in CEA levels between pre- and post-operative blood samples in patients undergoing surgery for colorectal cancer liver metastases (<span class="html-italic">p</span> &lt; 0.001).</p> Full article ">Figure 3
<p>Disease-free survival (DFS) after liver surgery in patients with KRAS positive (red color) vs. negative (green color dotted line) pre-operative plasma samples.</p> Full article ">Figure 4
<p>Overall survival (OS) after liver surgery for all patients with low (green color dotted line) vs. high (red color) KRAS fractional abundance in pre-operative plasma samples (cut-off 3.33%).</p> Full article ">Figure 5
<p>Disease-free survival (DFS) after liver surgery in patients with combined KRAS liver metastasis tissue and preoperative plasma positivity (red color) vs. tissue positivity only (green color dotted line).</p> Full article ">Figure 6
<p>Disease-free survival (DFS) after liver surgery for patients with low (green color dotted line) vs. high (red color) preoperative CEA level (cut-off 4.9 µg/L).</p> Full article ">Figure 7
<p>Overall survival (OS) after liver surgery for patients with low (green color dotted line) vs. high (red color) preoperative CEA level (cut-off 4.9 µg/L).</p> Full article ">Figure 8
<p>Overall survival (OS) after liver surgery for patients with combined low (green color dotted line) vs. high (red color) preoperative KRAS pFA and CEA levels (cut-off 3.33% and 4.9 µg/L, resp.).</p> Full article ">Figure 9
<p>Disease-free survival (DFS) after liver surgery for patients with combined low (green color dotted line) vs. high (red color) preoperative KRAS pFA and CEA levels (cut-off 3.33% and 4.9 µg/L, resp.).</p> Full article ">
24 pages, 87099 KiB  
Article
An Integrative Omics Approach Reveals Involvement of BRCA1 in Hepatic Metastatic Progression of Colorectal Cancer
by Daniela Gerovska, Gorka Larrinaga, Jon Danel Solano-Iturri, Joana Márquez, Patricia García Gallastegi, Abdel-Majid Khatib, Gereon Poschmann, Kai Stühler, María Armesto, Charles H. Lawrie, Iker Badiola and Marcos J. Araúzo-Bravo
Cancers 2020, 12(9), 2380; https://doi.org/10.3390/cancers12092380 - 22 Aug 2020
Cited by 11 | Viewed by 3799
Abstract
(1) Background & Aims: The roles of different cells in the tumor microenvironment (TME) are critical to the metastatic process. The phenotypic transformation of the liver cells is one of the most important stages of the hepatic metastasis progression of colorectal cancer (CRC). [...] Read more.
(1) Background & Aims: The roles of different cells in the tumor microenvironment (TME) are critical to the metastatic process. The phenotypic transformation of the liver cells is one of the most important stages of the hepatic metastasis progression of colorectal cancer (CRC). Our aim was to identify the major molecules (i.e., genes, miRNAs and proteins) involved in this process. (2) Methods: We isolated and performed whole-genome analysis of gene, miRNA, and protein expression in three types of liver cells (Ito cells, Kupffer cells, and liver sinusoidal endothelial cells) from the TME of a murine model of CRC liver metastasis. We selected the statistically significant differentially expressed molecules using the Student’s t-test with Benjamini-Hochberg correction and performed functional statistically-significant enrichment analysis of differentially expressed molecules with hypergeometric distribution using the curated collection of molecular signatures, MSigDB. To build a gene-miRNA-protein network centered in Brca1, we developed a software package (miRDiana) that collects miRNA targets from the union of the TargetScan, MicroCosm, mirTarBase, and miRWalk databases. This was used to search for miRNAs targeting Brca1. We validated the most relevant miRNAs with real-time quantitative PCR. To investigate BRCA1 protein expression, we built tissue microarrays (TMAs) from hepatic metastases of 34 CRC patients. (3) Results: Using integrated omics analyses, we observed that the Brca1 gene is among the twenty transcripts simultaneously up-regulated in all three types of TME liver cells during metastasis. Further analysis revealed that Brca1 is the last BRCA1-associated genome surveillance complex (BASC) gene activated in the TME. We confirmed this finding in human reanalyzing transcriptomics datasets from 184 patients from non-tumor colorectal tissue, primary colorectal tumor and colorectal liver metastasis of the GEO database. We found that the most probable sequence of cell activation during metastasis is Endothelial→Ito→Kupffer. Immunohistochemical analysis of human liver metastases showed the BRCA1 protein was co-localized in Ito, Kupffer, and endothelial cells in 81.8% of early or synchronous metastases. However, in the greater part of the metachronous liver metastases, this protein was not expressed in any of these TME cells. (4) Conclusions: These results suggest a possible role of the co-expression of BRCA1 in Ito, Kupffer, and sinusoidal endothelial cells in the early occurrence of CRC liver metastases, and point to BRCA1 as a potential TME biomarker. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>Experimental design and global omics analysis. (<b>A</b>) Two groups of mice were inoculated with C26 murine colon cancer cells and with PBS (Control). After 15 days, the mice were perfused, and after PercollV R gradient centrifugation, three types of liver cells were collected, namely liver sinusoidal endothelial cells (E), Ito cells (I) and Kupffer cells (K), from control (C) and TME (T), and isolated to perform omics experiments (gene expression, miRNA expression microarrays and proteomics). TP and TM denote the CRC primary and tumor liver metastasis cells, respectively. (<b>B</b>) Cell purity was checked via immunochemistry using specific antibodies to detect endothelial (CD146), Kupffer (CD68), and Ito (ASMA) cells. (<b>C</b>–<b>E</b>) PCA plots of mRNA, protein and miRNA expression. Red, blue, and green symbols mark endothelial, Kupffer, and Ito cells, respectively. TME cells are depicted with dodecahedra, and controls with spheres. For each mRNA sample we used 4 biological replicates; for each miRNA sample 3 biological replicates, except 2 for ECs and KTs; for the proteomics data we used 9 biological replicates for ECs, 7 for ETs, 6 for ICs and ITs, and 5 for KCs and KTs.</p> Full article ">Figure 2
<p>Differentially expressed miRNAs (DEMs) between control and TME cells. Heatmaps of the expression of the 20 top-ranked in decreasing order of significance, TME DEMs: (<b>A</b>–<b>C</b>) down-regulated, and (<b>F</b>–<b>H</b>) up-regulated, in endothelial, Ito, and Kupffer cells. Color bars codify miRNA expression on a log<sub>2</sub> scale. Higher miRNA expression corresponds to a redder color. Yellow frames mark the samples used to find the DEMs. The –log<sub>10</sub> (<span class="html-italic">p</span>-value) of the DEMs are presented in tables to the right of each heatmap. Euler-Venn diagrams of the (<b>D</b>) down-regulated and (<b>I</b>) up-regulated TME DEMs shared by the endothelial, Ito, and Kupffer cells are shown. Heatmaps of the expressions of the (<b>E</b>) fourteen miRNAs down-regulated and (<b>J</b>) two miRNAs up-regulated in the three types of TME cells are also shown. The –log<sub>10</sub> of the average of the <span class="html-italic">p</span>-values across the three cell type comparisons are presented in tables to the right of each heatmap. In all subplots, the samples are denoted with E, I, and K for endothelial, Ito, and Kupffer cells, C and T, for control and TME cells, and TP and TM denote the CRC primary and tumor liver metastasis cells, respectively. For each miRNA sample, we used 3 biological replicates except 2 for ECs and KTs.</p> Full article ">Figure 3
<p>Differentially expressed genes (DEGs) between control and TME cells. Heatmaps of the expression of the 20 top-ranked, in decreasing order of significance, TME DEGs: (<b>A</b>–<b>C</b>) down-regulated, and (<b>F</b>–<b>H</b>) up-regulated, in endothelial, Ito, and Kupffer cells. Color bars codify the gene expression on a log<sub>2</sub> scale. Higher gene expression corresponds to a redder color. Yellow frames mark the samples used to find the DEGs. The –log<sub>10</sub> (<span class="html-italic">p</span>-value) of the DEGs are presented in tables to the right of each heatmap. Euler-Venn diagrams of the (<b>D</b>) down-regulated and (<b>I</b>) up-regulated TME DEMs shared by the endothelial, Ito, and Kupffer cells are shown. Heatmaps of the expressions of the (<b>E</b>) eleven genes down-regulated and (<b>J</b>) twenty genes up-regulated in the three types of TME cells are also shown. The –log<sub>10</sub> of the average of the <span class="html-italic">p</span>-values across the three cell type comparisons are presented in tables to the right of each heatmap. In all subplots, the samples are denoted with E, I, and K for endothelial, Ito, and Kupffer cells, C and T for the control and TME cells, and TP and TM denote the CRC primary and tumor liver metastasis cells, respectively. For each mRNA sample, we used 4 biological replicates.</p> Full article ">Figure 4
<p>Gene expression correlation with <span class="html-italic">Brca1</span>. Heatmaps of the expression of the 50 top-ranked genes: (<b>A</b>) negatively or (<b>C</b>) positively correlated with the expression of <span class="html-italic">Brca1 a</span>cross all samples. Color bars codify the gene expression on a log2 scale. Higher gene expression corresponds to a redder color. Yellow frames mark the samples used to calculate the correlations. (<b>B</b>) Bar plots of the gene-expression correlation with <span class="html-italic">Brca1</span>. The central panel depicts the correlation of the expressions of all genes with the expression of <span class="html-italic">Brca1</span>. Left and right panels represent the correlation of the top 50 negatively- and positively-correlated genes, respectively. Green and red colors represent negatively- and positively-correlated genes, respectively. (<b>D</b>) Heatmap of the expression of the known Brca1-related miRNAs [<a href="#B24-cancers-12-02380" class="html-bibr">24</a>]. T: miRNAs targeting Brca1, U: miRNAs up-regulated by Brca1, D: miRNAs down-regulated by Brca1. (<b>E</b>) Violin plots of the expression distribution of the Brca1-related miRNAs. Black crosses represent mean positions. Black points represent the spread of the expression of the genes used to build the distributions. The samples are denoted with E, I, and K for endothelial, Ito, and Kupffer cells, C and T for control and TME cells, and TP and TM denote the CRC primary and tumor liver metastasis cells, respectively. For each mRNA sample, we used 4 biological replicates, and for each miRNA sample 3 biological replicates, except 2 for ECs and KTs.</p> Full article ">Figure 5
<p>Proposed gene-miRNA-protein network centered in <span class="html-italic">Brca1</span>. (<b>A</b>) The network center is the gene expression level of <span class="html-italic">Brca1</span>. The concentric rings from the center towards the periphery present the expression level of the miRNAs targeting <span class="html-italic">Brca1</span>, the protein level of the proteins targeted by such miRNAs, and the expression level of the genes targeted by such miRNAs (the last ring is double), respectively. Each molecule (gene, miRNA, protein) is represented by a rectangle with six colors codifying the expression of the samples in the order given by the legend frame. Higher gene expression corresponds to redder color. Violin plots in endothelial (<b>B</b>), Ito (<b>C</b>), and Kupffer (<b>D</b>) of the distribution of the down- and up-regulated molecules in tumor vs. the control of DEGs, DEMs, and DEPs in all the data and in <span class="html-italic">Brca1</span>, miRNA targeting <span class="html-italic">Brca1</span>, in proteins, and in genes targeted by such miRNAs. For each mRNA sample, we used 4 biological replicates; for each miRNA sample, 3 biological replicates, except 2 for ECs and KTs; for the proteomics data, 9 biological replicates for ECs, 7 for ETs, 6 for ICs and ITs, and 5 for KCs and KTs.</p> Full article ">Figure 6
<p><span class="html-italic">BRCA1</span> is the last BASC gene activated in TME. Heatmap of the expression of BASC-related genes in (<b>A</b>) mouse liver cell samples. The samples are denoted with E, I, and K for endothelial, Ito, and Kupffer cells, C and T for control and TME cells, and TP and TM denote the CRC primary and tumor liver metastasis cells, respectively. Higher gene expression corresponds to a redder color (for each mRNA sample, we used 4 biological replicates); and (<b>B</b>) human non-tumor colorectal tissue, primary colorectal tumor, and colorectal liver metastasis from 51 patients [<a href="#B39-cancers-12-02380" class="html-bibr">39</a>]. Higher gene expression corresponds to a redder color. (<b>C</b>) Violin plot of the expression distribution of human BASC-related genes. Black crosses represent mean positions. Black points represent the spread of the expression of the genes used to build the distributions. (<b>D</b>) Heatmap of the expression of BASC-related genes in human primary colorectal tumor and colorectal liver metastasis from 133 patients [<a href="#B40-cancers-12-02380" class="html-bibr">40</a>]. Higher gene expression corresponds to a redder color.</p> Full article ">Figure 7
<p>BRCA1 co-localization in TME cells from human CRC liver metastases. (<b>A</b>) The percentage of simultaneous BRCA1 expression in endothelial, Ito, and Kupffer cells significantly increases in metastases from Stage IV tumors (synchronous) compared to Stage I and II ones (metachronous). Positive = Co-expression of BRCA1 protein in the three TME cell types. Negative = No expression of BRCA1 in any TME cell type. (<b>B</b>) BRCA1 expression is co-localized on Ito, Kupffer, and endothelial cells from liver metastases from CRC categorized as Stage IV at first diagnosis (synchronous). White lines delimit the tumor cell tissue regions (T) from the non-tumoral cell stromal area (S). The last row shows the hematoxylin and eosin staining images.</p> Full article ">Figure 8
<p>The BRCA1 protein is not expressed in all the TME cells from CRC liver metastases from Stage I patients (metachronous). BRCA1 expression on TMA samples on Ito, Kupffer, and endothelial cells from human CRC liver metastases. White lines delimit the tumor cell tissue regions (T) from the non-tumoral cell stromal area (S).</p> Full article ">
12 pages, 1276 KiB  
Article
Correlation of RECIST, Computed Tomography Morphological Response, and Pathological Regression in Hepatic Metastasis Secondary to Colorectal Cancer: The AVAMET Study
by Ruth Vera, María Luisa Gómez, Juan Ramón Ayuso, Joan Figueras, Pilar García-Alfonso, Virginia Martínez, Adelaida Lacasta, Ana Ruiz-Casado, María José Safont, Jorge Aparicio, Juan Manuel Campos, Juan Carlos Cámara, Marta Martín-Richard, Clara Montagut, Carles Pericay, Jose María Vieitez, Esther Falcó, Mónica Jorge, Miguel Marín, Mercedes Salgado and Antonio Viúdezadd Show full author list remove Hide full author list
Cancers 2020, 12(8), 2259; https://doi.org/10.3390/cancers12082259 - 12 Aug 2020
Cited by 11 | Viewed by 2866
Abstract
Background: The prospective phase IV AVAMET study was undertaken to correlate response evaluation criteria in solid tumors (RECIST)-defined response rates with computed tomography-based morphological criteria (CTMC) and pathological response after liver resection of colorectal cancer metastases. Methods: Eligible patients were aged [...] Read more.
Background: The prospective phase IV AVAMET study was undertaken to correlate response evaluation criteria in solid tumors (RECIST)-defined response rates with computed tomography-based morphological criteria (CTMC) and pathological response after liver resection of colorectal cancer metastases. Methods: Eligible patients were aged ≥18 years, with Eastern Cooperative Oncology Group (ECOG) performance status 0/1 and histologically-confirmed colon or rectal adenocarcinoma with measurable liver metastases. Preoperative treatment was bevacizumab (7.5 mg on day 1) + XELOX (oxaliplatin 130 mg/m2, capecitabine 1000 mg/m2 bid on days 1–14 q3w). After three cycles, response was evaluated by a multidisciplinary team. Patients who were progression-free and metastasectomy candidates received one cycle of XELOX before undergoing surgery 3–5 weeks later, followed by four cycles of bevacizumab + XELOX. Results: A total of 83 patients entered the study; 68 were eligible for RECIST, 67 for CTMC, and 51 for pathological response evaluation. Of these patients, 49% had a complete or partial RECIST response, 91% had an optimal or incomplete CTMC response, and 81% had a complete or major pathological response. CTMC response predicted 37 of 41 pathological responses versus 23 of 41 responses predicted using RECIST (p = 0.008). Kappa coefficients indicated a lack of correlation between the results of RECIST and morphological responses and between morphological and pathological response rates. Conclusion: CTMC may represent a better marker of pathological response to bevacizumab + XELOX than RECIST in patients with potentially-resectable CRC liver metastases. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>Patient flow. CTMC, computed tomography-based morphological criteria; ITT, intent to treat; RECIST, response evaluation criteria in solid tumors; XELOX, capecitabine plus oxaliplatin.</p> Full article ">Figure 2
<p>Correlation of response data in patients with morphological, pathological, and radiological response data (<span class="html-italic">n =</span> 51). RECIST, response evaluation criteria in solid tumors.</p> Full article ">Figure 3
<p>Overall survival in all patients (<span class="html-italic">n</span> = 83).</p> Full article ">
13 pages, 889 KiB  
Article
Single Nucleotide Polymorphisms in MiRNA Binding Sites of Nucleotide Excision Repair-Related Genes Predict Clinical Benefit of Oxaliplatin in FOLFOXIRI Plus Bevacizumab: Analysis of the TRIBE Trial
by Mitsukuni Suenaga, Marta Schirripa, Shu Cao, Wu Zhang, Dongyun Yang, Chiara Cremolini, Sabina Murgioni, Sara Lonardi, Yan Ning, Satoshi Okazaki, Martin D. Berger, Yuji Miyamoto, Afsaneh Barzi, Fotios Loupakis, Alfredo Falcone and Heinz-Josef Lenz
Cancers 2020, 12(7), 1742; https://doi.org/10.3390/cancers12071742 - 30 Jun 2020
Cited by 6 | Viewed by 2576
Abstract
Background: The nucleotide excision repair (NER) pathway participates in platinum-induced DNA damage repair. Single nucleotide polymorphisms (SNPs) in miRNA-binding sites in the NER genes RPA2 and GTF2H1 are associated with the risk of colorectal cancer (CRC). Here, we analyzed whether RPA2 and GTF2H1 [...] Read more.
Background: The nucleotide excision repair (NER) pathway participates in platinum-induced DNA damage repair. Single nucleotide polymorphisms (SNPs) in miRNA-binding sites in the NER genes RPA2 and GTF2H1 are associated with the risk of colorectal cancer (CRC). Here, we analyzed whether RPA2 and GTF2H1 SNPs predict the efficacy of oxaliplatin in metastatic CRC (mCRC) patients. Patients and methods: Genomic DNA was extracted from blood samples from 457 patients with mCRC enrolled in the TRIBE trial, which compared first-line FOLFOXIRI plus bevacizumab (BEV) (n = 230, discovery cohort) and first-line FOLFIRI plus BEV (n = 227, control cohort). SNPs were analyzed by PCR-based direct sequencing. Results: In the FOLFOXIRI + BEV-treated cohort expressing wild-type KRAS, progression-free survival (PFS) was shorter for the RPA2 rs7356 C/C variant subgroup than the any T allele subgroup in univariate analysis (9.1 versus 13.3 months respectively, hazard ratio (HR) 2.32, 95% confidence interval (CI): 1.07–5.03, p = 0.020) and this remained significant in multivariable analysis (HR 2.97, 95%CI: 1.27–6.94, p = 0.012). A similar trend was observed for overall survival. In contrast, patients expressing mutant RAS and RPA2 rs7356 C/C variant had longer PFS with FOLFOXIRI + BEV than with FOLFIRI + BEV (12.1 versus 7.6 months, HR 0.23, 95%CI: 0.09–0.62, p = 0.002) but no superiority of FOLFOXIRI + BEV was observed for the RAS mutant, RPA2 rs7356 any T variant subgroup (11.7 versus 9.6 months, HR 0.77, 95%CI: 0.56–1.07, p = 0.12) or the RAS wild-type, RPA2 rs7356 C/C variant subgroup. Conclusion: RPA2 SNPs may serve as predictive and prognostic markers of oxaliplatin responsiveness in a RAS status-dependent manner in mCRC patients receiving FOLFOXIRI + BEV. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>Single nucleotide polymorphisms (SNPs) and clinical outcomes. Progression-free survival (PFS) and/or overall survival (OS) by <span class="html-italic">GTF2H1</span> rs4596 variants, G/G (<b><span style="color:#0024C2">―</span></b>) or any C (<b><span style="color:#00FA00">―</span></b>) in the discovery cohort (<b>A,B</b>), and by <span class="html-italic">RPA2</span> rs7356 variant, C/C (<b><span style="color:#00FA00">―</span></b>) or any T (<b><span style="color:#0432FF">―</span></b>) in <span class="html-italic">KRAS</span> wild-type subgroup in the discovery cohort (<b>C,D</b>).</p> Full article ">Figure 2
<p>Progression-free survival (PFS) according to <span class="html-italic">RPA2</span> rs7356 variants, C/C or any T in the discovery cohort (<b><span style="color:#00FA00">―</span></b>) and the control cohort (<b><span style="color:#0432FF">―</span></b>): C/C, RAS mutant (<b>A</b>), Any T, RAS mutant (<b>B</b>), C/C, <span class="html-italic">RAS</span> wild-type (<b>C</b>), Any T, <span class="html-italic">RAS</span> wild-type (<b>D</b>).</p> Full article ">
9 pages, 752 KiB  
Article
The Role of Anti-Angiogenics in Pre-Treated Metastatic BRAF-Mutant Colorectal Cancer: A Pooled Analysis
by Fabio Gelsomino, Andrea Casadei-Gardini, Daniele Rossini, Alessandra Boccaccino, Gianluca Masi, Chiara Cremolini, Andrea Spallanzani, Massimo Giuseppe Viola, Ingrid Garajovà, Massimiliano Salati, Maria Teresa Elia, Francesco Caputo, Chiara Santini, Alfredo Falcone, Stefano Cascinu and Emiliano Tamburini
Cancers 2020, 12(4), 1022; https://doi.org/10.3390/cancers12041022 - 21 Apr 2020
Cited by 16 | Viewed by 3531
Abstract
Background. FOLFOXIRI plus Bevacizumab is one of the most frequently used first-line treatments for patients with BRAF-mutant colorectal cancer (CRC), while second-line treatment requires extensive further research. In this pooled analysis, we evaluate the impact of anti-angiogenics in patients with pre-treated [...] Read more.
Background. FOLFOXIRI plus Bevacizumab is one of the most frequently used first-line treatments for patients with BRAF-mutant colorectal cancer (CRC), while second-line treatment requires extensive further research. In this pooled analysis, we evaluate the impact of anti-angiogenics in patients with pre-treated BRAF-mutant CRC. Methods. We monitored patients in randomized, controlled studies who had advanced CRC and were undergoing second-line chemotherapy in addition to utilizing Bevacizumab, Ramucirumab or Aflibercept treatments. These data were pooled together with the data and results of BRAF-mutant patients enrolled in two phase III trials (TRIBE and TRIBE-2 study), who had been treated with second-line treatment both with or without Bevacizumab. Overall survival (OS), in relation to BRAF mutational status, was the primary focus. Results. Pooled analysis included 129 patients. Anti-angiogenics were found to have a significant advantage over the placebo in terms of OS (HR 0.50, 95%CI 0.29–0.85) (p = 0.01). Conclusions. Our pooled analysis confirms the efficacy of anti-angiogenics in pre-treated BRAF-mutant CRC, establishing the combination of chemotherapy plus Bevacizumab or Ramucirumab or Aflibercept as a valid treatment option. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>Summary of the evidence search and selection process (Flow diagram).</p> Full article ">Figure 2
<p>Funnel plots of publication bias.</p> Full article ">Figure 3
<p>Forest plot of antiangiogenics versus no antiangiogenics in terms of OS in patients with <span class="html-italic">BRAF</span> mutation.</p> Full article ">
11 pages, 1190 KiB  
Article
Effectiveness and Costs Associated to Adding Cetuximab or Bevacizumab to Chemotherapy as Initial Treatment in Metastatic Colorectal Cancer: Results from the Observational FABIO Project
by Matteo Franchi, Donatella Garau, Ursula Kirchmayer, Mirko Di Martino, Marilena Romero, Ilenia De Carlo, Salvatore Scondotto and Giovanni Corrao
Cancers 2020, 12(4), 839; https://doi.org/10.3390/cancers12040839 - 31 Mar 2020
Cited by 11 | Viewed by 3003
Abstract
Evidence available on the effectiveness and costs of biological therapies for the initial treatment of metastatic colorectal cancer (mCRC) is scarce and contrasting. We conducted a population-based cohort investigation for assessing overall survival and costs associated with their use in a real-world setting. [...] Read more.
Evidence available on the effectiveness and costs of biological therapies for the initial treatment of metastatic colorectal cancer (mCRC) is scarce and contrasting. We conducted a population-based cohort investigation for assessing overall survival and costs associated with their use in a real-world setting. Healthcare utilization databases were used to select patients newly diagnosed with mCRC between 2010 and 2016. Those initially treated with biological therapy (bevacizumab or cetuximab) added to chemotherapy were propensity-score-matched to those treated with standard chemotherapy alone, and were followed up to June 30th, 2018. Kaplan–Meier survival estimates, restricted mean survival time (RMST) and cumulative costs were compared between the two treatment arms. The study cohort included 1896 mCRC patients treated with biological therapy matched to 5678 patients treated with chemotherapy alone. Median overall survival was 21.8 and 20.2 months, respectively. After 84 months of follow-up, RMSTs were 30.9 and 31.9 months (p = 0.193), indicating no differences between the average survival time between treatment arms. Patients treated with biological therapy were associated with higher costs. Cumulative per capita costs were €59,663 and €44,399, respectively. In our study, first-line biological therapy did not improve long-term overall survival and was associated with higher costs as compared to standard chemotherapy. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>Flowchart of inclusion and exclusion criteria. FABIO project, Italy, 2010–2016.</p> Full article ">Figure 2
<p>Comparison between Kaplan–Meier overall survival curves of metastatic colorectal cancer cohort members on first-line treatment with biologic-based (bevacizumab or cetuximab, Bio + CT) or standard chemotherapy (CT) alone. FABIO project, Italy, 2010–2016.</p> Full article ">Figure 3
<p>Comparison between cumulative per capita healthcare costs sustained by the NHS for caring for metastatic colorectal cancer cohort members on first-line treatment with biologic-based (bevacizumab or cetuximab, Bio + CT) or standard chemotherapy (CT) alone. FABIO project, Italy, 2010–2016.</p> Full article ">Figure 4
<p>Incremental cost-effectiveness ratio (ICER) scatterplot comparing metastatic colorectal cancer cohort members on first-line treatment with biologic-based (bevacizumab or cetuximab, Bio + CT) or standard chemotherapy (CT) alone. FABIO project, Lombardy Region, 2010–2014.</p> Full article ">
10 pages, 534 KiB  
Article
An Easy-To-Use Survival Score Compared to Existing Tools for Older Patients with Cerebral Metastases from Colorectal Cancer
by Dirk Rades, Trang Nguyen, Stefan Janssen and Steven E. Schild
Cancers 2020, 12(4), 833; https://doi.org/10.3390/cancers12040833 - 30 Mar 2020
Cited by 5 | Viewed by 2355
Abstract
An easy-to-use survival score was developed specifically for older patients with cerebral metastases from colorectal cancer, and was compared to existing tools regarding the accuracy of identifying patients who die in ≤6 months and those who survive for ≥6 months. The new score [...] Read more.
An easy-to-use survival score was developed specifically for older patients with cerebral metastases from colorectal cancer, and was compared to existing tools regarding the accuracy of identifying patients who die in ≤6 months and those who survive for ≥6 months. The new score was built from 57 patients receiving whole-brain irradiation. It included three groups identified from 6-month survival rates based on two independent predictors (performance status and absence/presence of non-cerebral metastases), with 6-month survival rates of 0% (0 points), 26% (1 point), and 75% (2 points), respectively. This score was compared to diagnosis-specific scores, namely the diagnosis-specific graded prognostic assessment (DS-GPA), the Dziggel-Score and the WBRT-30-CRC (whole-brain radiotherapy with 30 Gy in 10 fractions for cerebral metastases from colorectal cancer) score and to a non-diagnosis-specific score for older persons (Evers-Score). Positive predictive values were 100% (new score), 87% (DS-GPA), 86% (Dziggel-Score), 91% (WBRT-30-CRC), and 100% (Evers-Score), respectively, for patients dying ≤6 months, and 75%, 33%, 75%, 60%, and 45%, respectively, for survivors ≥6 months. Of the five tools, the new score and the Evers-Score were most precise in identifying patients dying ≤6 months. The new score and the Dziggel-Scores were best at identifying patients surviving ≥6 months. When combining the results, the new score appeared preferable to the existing tools. The score appears not necessary for patients with additional liver metastases, since their 6-month survival rate was 0%. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>Kaplan–Meier curves of the three groups for the new score.</p> Full article ">
13 pages, 2727 KiB  
Article
Autocatalytic Tissue Polymerization Reaction Mechanism in Colorectal Cancer Development and Growth
by Bruce M. Boman, Arthur Guetter, Ryan M. Boman and Olaf A. Runquist
Cancers 2020, 12(2), 460; https://doi.org/10.3390/cancers12020460 - 17 Feb 2020
Cited by 3 | Viewed by 3305
Abstract
The goal of our study was to measure the kinetics of human colorectal cancer (CRC) development in order to identify aberrant mechanisms in tissue dynamics and processes that contribute to colon tumorigenesis. The kinetics of tumor development were investigated using age-at-tumor diagnosis (adenomas [...] Read more.
The goal of our study was to measure the kinetics of human colorectal cancer (CRC) development in order to identify aberrant mechanisms in tissue dynamics and processes that contribute to colon tumorigenesis. The kinetics of tumor development were investigated using age-at-tumor diagnosis (adenomas and CRCs) of familial adenomatous coli (FAP) patients and sporadic CRC patients. Plots of age-at-tumor diagnosis data as a function of age showed a distinct sigmoidal-shaped curve that is characteristic of an autocatalytic reaction. Consequently, we performed logistics function analysis and found an excellent fit (p < 0.05) of the logistic equation to the curves for age-at-tumor diagnoses. These findings indicate that the tissue mechanism that becomes altered in CRC development and growth involves an autocatalytic reaction. We conjecture that colonic epithelium normally functions as a polymer of cells which dynamically maintains itself in a steady state through an autocatalytic polymerization mechanism. Further, in FAP and sporadic CRC patients, mutation in the adenomatous polyposis coli (APC) gene increases autocatalytic tissue polymerization and induces tumor tissues to autocatalyze their own progressive growth, which drives tumor development in the colon. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>Age at colonic tumor development in familial adenomatous coli (FAP) patients.</p> Full article ">Figure 2
<p>Age at colonic tumor development in sporadic tumor patients.</p> Full article ">Figure 3
<p>Fitting age-at-adenoma diagnosis data on FAP patients using the logistic equation.</p> Full article ">Figure 4
<p>Fitting age-at-adenoma diagnosis data on sporadic tumor patients using the logistic equation.</p> Full article ">Figure 5
<p>Fitting age-at-colorectal cancer (CRC) diagnosis data on FAP patients using the logistic equation.</p> Full article ">Figure 6
<p>Fitting age-at-CRC diagnosis data on sporadic tumor patients using the logistic equation.</p> Full article ">
12 pages, 1093 KiB  
Article
Small RNA Profiling of piRNAs in Colorectal Cancer Identifies Consistent Overexpression of piR-24000 That Correlates Clinically with an Aggressive Disease Phenotype
by Deepak Narayanan Iyer, Timothy Ming-Hun Wan, Johnny Hon-Wai Man, Ryan Wai-Yan Sin, Xue Li, Oswens Siu-Hung Lo, Dominic Chi-Chung Foo, Roberta Wen-Chi Pang, Wai-Lun Law and Lui Ng
Cancers 2020, 12(1), 188; https://doi.org/10.3390/cancers12010188 - 12 Jan 2020
Cited by 28 | Viewed by 3608
Abstract
Piwi-interacting RNAs (piRNAs) represent a novel class of small non-coding RNAs (ncRNAs) that have been shown to have a deregulated expression in several cancers, although their clinical significance in colorectal cancer (CRC) remains unclear. With an aim of delineating the piRNA distribution in [...] Read more.
Piwi-interacting RNAs (piRNAs) represent a novel class of small non-coding RNAs (ncRNAs) that have been shown to have a deregulated expression in several cancers, although their clinical significance in colorectal cancer (CRC) remains unclear. With an aim of delineating the piRNA distribution in CRC, we conducted a systematic discovery and validation of piRNAs within two clinical cohorts. In the discovery phase, we profiled tumor and adjacent normal tissues from 18 CRC patients by deep sequencing and identified a global piRNA downregulation in CRC. Moreover, we identified piR-24000 as an unexplored piRNA that was significantly overexpressed in CRC. Using qPCR, we validated the overexpression of piR-24000 in 87 CRC patients. Additionally, we identified a significant association between a high expression of piR-24000 and an aggressive CRC phenotype including poor differentiation, presence of distant metastases, and a higher stage. Lastly, ROC analysis demonstrated a strong diagnostic power of piR-24000 in discriminating CRC patients from normal subjects. Taken together, this study provides one of the earliest large-scale reports of the global distribution of piRNAs in CRC. In addition, piR-24000 was identified as a likely oncogene in CRC that can serve as a biomarker or a therapeutic target. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>Hierarchical clustering of differentially expressed piRNAs in colorectal cancer. A total of 143 differentially expressed piRNAs (−2 ≥ fold-change ≥ 2; <span class="html-italic">p</span> &lt; 0.05) in colorectal cancer (CRC) vs. non-malignant colon tissue were hierarchically clustered together using an average-linkage-based cluster distance metric and Pearson correlation as the point distance metric. Rows represent tissue specimens (Blue—normal tissue; Red—tumor tissue), while the columns represent the differentially expressed piRNAs. As per the Z-score color coding, red represents a high expression, whereas green represents a low expression of a given piRNA.</p> Full article ">Figure 2
<p>Expression of <span class="html-italic">piR-24000</span> in the discovery cohort. Expression levels (counts) of <span class="html-italic">piR-24000</span> in tumor samples compared with the adjacent non-malignant colon tissue.</p> Full article ">Figure 3
<p><span class="html-italic">piR-24000</span> is overexpressed in CRC. Real-time PCR-based expression analysis of <span class="html-italic">piR-24000</span> in (<b>A</b>) matched CRC, adenoma, and normal colon tissues from 12 patients, (<b>B</b>) matched CRC and adjacent normal colonic mucosa from 87 patients. Expression of <span class="html-italic">piR-24000</span> was normalized to <span class="html-italic">RNU6B</span> and expressed as −∆Ct (negative delta Ct).</p> Full article ">Figure 4
<p>Expression of <span class="html-italic">piR-24000</span> in normal colonic mucosa and metastatic subtypes of CRC. Real-time PCR-based expression analysis of <span class="html-italic">piR-24000</span> in normal colonic tissue (<span class="html-italic">N</span> = 87), non-metastatic CRC tissue (CRC-M0; <span class="html-italic">N</span> = 66), metastatic CRC tissue (CRC-M1; <span class="html-italic">N</span> = 21), and distant liver metastases (Mets; <span class="html-italic">N</span> = 20). Expression of <span class="html-italic">piR-24000</span> was normalized to <span class="html-italic">RNU6B</span> and expressed as −∆Ct (negative delta Ct).</p> Full article ">Figure 5
<p>Assessment of the diagnostic performance of <span class="html-italic">piR-24000</span> in CRC. A standard receiver operating characteristic (ROC) curve was plotted for <span class="html-italic">piR-24000</span> to interpret its accuracy in discriminating CRC patients and control subjects in the following groups: (<b>A</b>) all patients combined, (<b>B</b>) early-stage CRC patients (stage I and II, <span class="html-italic">n</span> = 33), and (<b>C</b>) late-stage CRC patients (stage III and IV, <span class="html-italic">n</span> = 54).</p> Full article ">

Review

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27 pages, 654 KiB  
Review
Immune Checkpoint Inhibitors in pMMR Metastatic Colorectal Cancer: A Tough Challenge
by Federica Marmorino, Alessandra Boccaccino, Marco Maria Germani, Alfredo Falcone and Chiara Cremolini
Cancers 2020, 12(8), 2317; https://doi.org/10.3390/cancers12082317 - 17 Aug 2020
Cited by 40 | Viewed by 6396
Abstract
The introduction of checkpoint inhibitors provided remarkable achievements in several solid tumors but only 5% of metastatic colorectal cancer (mCRC) patients, i.e., those with bearing microsatellite instable (MSI-high)/deficient DNA mismatch repair (dMMR) tumors, benefit from this approach. The favorable effect of immunotherapy in [...] Read more.
The introduction of checkpoint inhibitors provided remarkable achievements in several solid tumors but only 5% of metastatic colorectal cancer (mCRC) patients, i.e., those with bearing microsatellite instable (MSI-high)/deficient DNA mismatch repair (dMMR) tumors, benefit from this approach. The favorable effect of immunotherapy in these patients has been postulated to be due to an increase in neoantigens due to their higher somatic mutational load, also associated with an abundant infiltration of immune cells in tumor microenvironment (TME). While in patients with dMMR tumors checkpoint inhibitors allow achieving durable response with dramatic survival improvement, current results in patients with microsatellite stable (MSS or MSI-low)/proficient DNA mismatch repair (pMMR) tumors are disappointing. These tumors show low mutational load and absence of “immune-competent” TME, and are intrinsically resistant to immune checkpoint inhibitors. Modifying the interplay among cancer cells, TME and host immune system is the aim of multiple lines of research in order to enhance the immunogenicity of pMMR mCRC, and exploit immunotherapy also in this field. Here, we focus on the rationale behind ongoing clinical trials aiming at extending the efficacy of immunotherapy beyond the MSI-high/dMMR subgroup with particular regard to academic no-profit studies. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>Approaches to enhance immunogenicity of proficient mismatch repair (pMMR) colorectal cancer. CTL: cytotoxic Lymphocytes; BRAFi: BRAF inhibitors; EGFRi: EGFR inhibitors; MEKi: MEK inhibitors; TME: Tumor Microenvironment.</p> Full article ">
21 pages, 1155 KiB  
Review
Immune-Modulating Effects of Conventional Therapies in Colorectal Cancer
by Erta Kalanxhi, Sebastian Meltzer and Anne Hansen Ree
Cancers 2020, 12(8), 2193; https://doi.org/10.3390/cancers12082193 - 6 Aug 2020
Cited by 6 | Viewed by 2777
Abstract
Biological heterogeneity and low inherent immunogenicity are two features that greatly impact therapeutic management and outcome in colorectal cancer. Despite high local control rates, systemic tumor dissemination remains the main cause of treatment failure and stresses the need for new developments in combined-modality [...] Read more.
Biological heterogeneity and low inherent immunogenicity are two features that greatly impact therapeutic management and outcome in colorectal cancer. Despite high local control rates, systemic tumor dissemination remains the main cause of treatment failure and stresses the need for new developments in combined-modality approaches. While the role of adaptive immune responses in a small subgroup of colorectal tumors with inherent immunogenicity is indisputable, the challenge remains in identifying the optimal synergy between conventional treatment modalities and immune therapy for the majority of the less immunogenic cases. In this context, cytotoxic agents such as radiation and certain chemotherapeutics can be utilized to enhance the immunogenicity of an otherwise immunologically silent disease and enable responsiveness to immune therapy. In this review, we explore the immunological characteristics of colorectal cancer, the effects that standard-of-care treatments have on the immune system, and the opportunities arising from combining immune checkpoint-blocking therapy with immune-modulating conventional treatments. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>The concept of immunogenic cell death by oxaliplatin. Cytotoxic damage by oxaliplatin (1) causes release of tumor antigens from the dying tumor (2). These are taken up (3) by dendritic cells (DC) and presented to cytotoxic T-cells (4), resulting in their activation and clonal proliferation (5). This will in principle enable specific T-cell-targeting of any tumor manifestation systemically (6).</p> Full article ">Figure 2
<p>Tumor-defeating immunity under neoadjuvant cytotoxic therapy in high-risk rectal cancer. Short-course induction chemotherapy and sequential chemoradiotherapy in locally advanced rectal cancer cause repetitive myelosuppression and a resulting replenishment of the hematopoietic cell pool (1) when both treatment modalities contain oxaliplatin. The enhanced recruitment of maturing dendritic cells (2) enables the presentation of tumor antigens, released from the dying tumor, to cytotoxic T-cells (3), which after clonal expansion (4) may eliminate microscopic tumor cells at distant sites in the patient at high risk of metastatic progression.</p> Full article ">Figure 3
<p>The METIMMOX study flow chart. Each treatment arm consists of intermittent sequences of active therapy over 8 cycles (16 weeks), before break until disease progression, when the therapy is reintroduced and administered for another 8 cycles before a new break. This “go-and-stop” schedule is continued until disease progression on ongoing therapy (defining progression-free survival in terms of failure of treatment strategy), intolerable toxicity, withdrawal of consent, or death, whichever occurs first. Circles indicate study visits with appendant activities. During a break period, radiographic assessment (CT), blood biobanking, and visits are done every 8 weeks until start of a new therapy sequence. Adverse events are recorded at each visit. Quality-of-life assessments are done before Week 1, at the end of Sequence 1 (Week 16), and at disease progression on study treatment. Timing for blood and biopsy biobanking and functional magnetic resonance imaging (fMRI) recordings is indicated.</p> Full article ">
17 pages, 1425 KiB  
Review
Harnessing Omics Approaches on Advanced Preclinical Models to Discovery Novel Therapeutic Targets for the Treatment of Metastatic Colorectal Cancer
by Manuela Porru, Pasquale Zizza, Nadia Panera, Anna Alisi, Annamaria Biroccio and Carlo Leonetti
Cancers 2020, 12(7), 1830; https://doi.org/10.3390/cancers12071830 - 8 Jul 2020
Cited by 3 | Viewed by 3035
Abstract
Metastatic colorectal cancer (mCRC) remains challenging because of the emergence of resistance mechanisms to anti-epidermal growth factor receptor (EGFR) therapeutics, so more effective strategies to improve the patients’ outcome are needed. During the last decade, the application of a multi-omics approach has contributed [...] Read more.
Metastatic colorectal cancer (mCRC) remains challenging because of the emergence of resistance mechanisms to anti-epidermal growth factor receptor (EGFR) therapeutics, so more effective strategies to improve the patients’ outcome are needed. During the last decade, the application of a multi-omics approach has contributed to a deeper understanding of the complex molecular landscape of human CRC, identifying a plethora of drug targets for precision medicine. Target validation relies on the use of experimental models that would retain the molecular and clinical features of human colorectal cancer, thus mirroring the clinical characteristics of patients. In particular, organoids and patient-derived-xenografts (PDXs), as well as genetically engineered mouse models (GEMMs) and patient-derived orthotopic xenografts (PDOXs), should be considered for translational purposes. Overall, omics and advanced mouse models of cancer represent a portfolio of sophisticated biological tools that, if optimized for use in concert with accurate data analysis, could accelerate the anticancer discovery process and provide new weapons against cancer. In this review, we highlight success reached following the integration of omics and experimental models; moreover, results produced by our group in the field of mCRC are also presented. Full article
(This article belongs to the Special Issue Metastatic Colorectal Cancer)
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<p>Schematic representation showing the main experimental models and OMICS approaches that can be integrated for the development of effective anticancer drugs. This figure was created with BioRender.com.</p> Full article ">Figure 2
<p>Gene expression analysis in patient-derived-xenografts (PDXs) and in HCT116 cells treated with EMICORON. (<b>A</b>) Heatmap representation of cancer-related genes analyzed by TaqMan OpenArray that were up-regulated (upper panel) or down-regulated genes (lower panel) in a responder PDX mouse model treated or untreated with EMICORON. (<b>B</b>) Heatmap representation of cancer-related genes analyzed by TaqMan OpenArray that were up-regulated (upper panel) or down-regulated genes (lower panel) in a non-responder PDX mouse model treated or untreated with EMICORON. (<b>C</b>) Heatmap representation of cancer-related genes analyzed by TaqMan OpenArray that were up-regulated (upper panel) or down-regulated genes (lower panel) in HCT116 cells that were treated or untreated with EMICORON.</p> Full article ">Figure 3
<p>Selection of target genes of EMICORON. (<b>A</b>) Venn diagrams showing the overlap between the genes up-regulated in the responder and non-responder PDX models following treatment with EMICORON (given orally at 15 mg/kg/mouse daily for two consecutive weeks). Eleven genes selectively upregulated in the responder mouse were selected as targets of EMICORON. (<b>B</b>) Venn diagrams showing the overlap between the genes down-regulated in the responder and non-responder PDXs treated with EMICORON (as above reported). The analysis identified 71 genes targets of EMICORON. (<b>C</b>) Venn diagrams showing the overlap between the genes selected in the panel A and the genes up-regulated in the HCT116 cells treated with EMICORON (1 µM for 24 h). The analysis identified 5 common genes that were selected as targets of EMICORON. (<b>D</b>) Venn diagrams showing the overlap between the genes selected in the panel B and the genes down-regulated in the HCT116 cells treated with EMICORON (1 µM for 24 h). The analysis identified 19 common genes selected as targets of EMICORON.</p> Full article ">
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