Genetic and Epigenetic Intra-tumour Heterogeneity in Colorectal Cancer

The role of a cuproptosis-related prognostic signature in colon cancer tumor microenvironment and immune responses

Background: Colon adenocarcinoma (COAD) is a common malignant tumor of the digestive tract with poor clinical outcomes. Cuproptosis is a novel cell death mechanism and linked to mitochondrial respiration. However, the role of cuproptosis in colon cancer tumor microenvironment (TME) and immune responses remains unknown.

Methods: We conducted difference analysis to identify the differential expressed cuproptosis-related genes (CRGs). According to the CRGs, the TCGA-COAD samples were categorized using consensus clustering. The LASSO regression analysis was utilized to develop the cuproptosis-related signature. We then verified the model reliability by Kaplan–Meier, PCA, and ROC analysis. The GES39582 cohort served as the validation set. GO and KEGG functional analyses were conducted to investigate the underlying mechanism. We compared the infiltration levels of immune cells, the expression levels of immune checkpoints, and microsatellite instability (MSI) status between the high- and low-risk groups. Additionally, the relationships between the risk signature and immune cells and cancer stem cell (CSC) were analyzed.

Results: Finally, we identified 9 differentially expressed CRGs in COAD. According to the expression of CRGs, the TCGA-COAD samples were separated into two clusters. The 11-gene signature was established by LASSO, and it had excellent predictive power for COAD prognosis. Besides, we used the GSE39582 cohort to validate the prognostic value of the model. GO and KEGG results demonstrated that the survival differences between two risk groups was mainly linked to the extracellular matrix (ECM). Further immune characterization analysis showed the significant differences in the immune cell infiltration and immune responses between two risk groups.

Conclusion: Overall, the novel cuproptosis-related signature was able to accurately predict COAD prognosis and played important roles in COAD tumor microenvironment and immune responses.

Identification of genes with high heterogeneity of expression as a predictor of different prognosis and therapeutic responses in colorectal cancer: a challenge and a strategy

Background

Molecular heterogeneity is one of the most important concerns in colorectal cancer (CRC), which results in a wide range of therapy responses and patient prognosis. We aimed to identify the genes with high heterogeneity of expression (HHE) and their relation with prognosis and drug resistance.

Methods

Two cohort studies, the cancer genome atlas (TCGA) and the GSE39582, were used to discover oncogenes genes with HHE. The relationship between identified genes with clinical and genomic characteristics was evaluated based on TCGA data. Also, the GDSC and CCLE data were used for drug resistance and sensitivity. Sixty CRC samples were used to validate the obtained data by RT-qPCR.

Results

Findings revealed that 132 genes with HHE were found to be up-regulated in both cohorts and were enriched in pathways such as hypoxia, angiogenesis, and metastasis. Forty-nine of selected genes related to clinical and genomic variables, including stage, common mutations, the tumor site, and microsatellite state that were ignored. The expression level of CXCL1, SFTA2, SELE, and SACS as genes with HHE were predicted survival patients, and RT-qPCR results demonstrated that levels of SELE and SACS had HHE in CRC samples. The expression of many identified genes like BGN, MMP7, COL11A1, FAP, KLK10, and TNFRSE11B was associated with resistance to chemotherapy drugs.

Conclusions

Some genes expression, including SELE, SACS, BGN, KLK10, COL11A1, and TNFRSE11B have an oncogenic function with HHE, and their expression can be used as indicators for differing treatment responses and survival rates in CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02694-9.

Application of mTORC1 Inhibitors for Tissue-Agnostic Management of Standard-Therapy-Refractory Solid Tumors

In this analysis, we examined the efficacy, feasibility, and limitations of the application of mTOR inhibitors based on the individual molecular profiles of pretreated cancer patients after the failure of all standard treatments in the palliative setting. In this single-center, real-world analysis of our platform for precision medicine, we analyzed the molecular characteristics of 71 cancer patients. The tumor samples of the patients were analyzed using next-generation sequencing panels of mutation hotspots, microsatellite stability testing, and immunohistochemistry. All profiles were reviewed by a multidisciplinary team to provide a targeted treatment recommendation after a consensus discussion. Seventy-one cancer patients with activation of the mTOR pathway were offered an mTORC1-inhibitor-based targeted therapy, and twenty-three (32.4%) of them eventually received the targeted therapy. Only three patients (4.2%) achieved stable disease, of whom one experienced progressive disease again after 9.1 months. The median time to treatment failure was 2.8 months. In total, 110 mutations were detected in 60 patients (84.5%). The three most frequent mutations were found in TP53, PTEN, and KRAS, which accounted for over 50% (56.4%) of all mutations. In sum, in selected patients with heavily pretreated solid tumors with activation of the mTOR pathway, the antitumoral activity of mTORC1 inhibition was weak.

Prediction of lymph node metastasis in early colorectal cancer based on histologic images by artificial intelligence

Risk evaluation of lymph node metastasis (LNM) for endoscopically resected submucosal invasive (T1) colorectal cancers (CRC) is critical for determining therapeutic strategies, but interobserver variability for histologic evaluation remains a major problem. To address this issue, we developed a machine-learning model for predicting LNM of T1 CRC without histologic assessment. A total of 783 consecutive T1 CRC cases were randomly split into 548 training and 235 validation cases. First, we trained convolutional neural networks (CNN) to extract cancer tile images from whole-slide images, then re-labeled these cancer tiles with LNM status for re-training. Statistical parameters of the tile images based on the probability of primary endpoints were assembled to predict LNM in cases with a random forest algorithm, and defined its predictive value as random forest score. We evaluated the performance of case-based prediction models for both training and validation datasets with area under the receiver operating characteristic curves (AUC). The accuracy for classifying cancer tiles was 0.980. Among cancer tiles, the accuracy for classifying tiles that were LNM-positive or LNM-negative was 0.740. The AUCs of the prediction models in the training and validation sets were 0.971 and 0.760, respectively. CNN judged the LNM probability by considering histologic tumor grade.

Personalized Immunotherapy in Colorectal Cancers: Where Do We Stand?

Colorectal cancer (CRC) is the second leading cause of cancer death in the world. Immunotherapy using monoclonal antibodies, immune-checkpoint inhibitors, adoptive cell therapy, and cancer vaccines has raised great hopes for treating poor prognosis metastatic CRCs that are resistant to the conventional therapies. However, high inter-tumor and intra-tumor heterogeneity hinder the success of immunotherapy in CRC. Patients with a similar tumor phenotype respond differently to the same immunotherapy regimen. Mutation-based classification, molecular subtyping, and immunoscoring of CRCs facilitated the multi-aspect grouping of CRC patients and improved immunotherapy. Personalized immunotherapy using tumor-specific neoantigens provides the opportunity to consider each patient as an independent group deserving of individualized immunotherapy. In the recent decade, the development of sequencing and multi-omics techniques has helped us classify patients more precisely. The expansion of such advanced techniques along with the neoantigen-based immunotherapy could herald a new era in treating heterogeneous tumors such as CRC. In this review article, we provided the latest findings in immunotherapy of CRC. We elaborated on the heterogeneity of CRC patients as a bottleneck of CRC immunotherapy and reviewed the latest advances in personalized immunotherapy to overcome CRC heterogeneity.

Mapping the colorectal tumor microbiota

The gut microbiome in patients with colorectal cancer (CRC) is different than that of healthy controls. Previous studies have profiled the CRC tumor microbiome using a single biopsy. However, since the morphology and cellular subtype vary significantly within an individual tumor, the possibility of sampling error arises for the microbiome within an individual tumor. To test this hypothesis, seven biopsies were taken from representative areas on and off the tumor in five patients with CRC. The microbiome composition was strikingly similar across all samples from an individual. The variation in microbiome alpha-diversity was significantly greater between individuals' samples then within individuals. This is the first study, to our knowledge, that shows that the microbiome of an individual tumor is spatially homogeneous. Our finding strengthens the assumption that a single biopsy is representative of the entire tumor, and that microbiota changes are not limited to a specific area of the neoplasm.

Evaluation of the Impact of Intratumoral Heterogeneity of Esophageal Cancer on Pathological Diagnosis and P16 Methylation and the Representativity of Endoscopic Biopsy

Background

P16 methylation is expected to be potential diagnostic and therapeutic targets for esophageal cancer (EC). The intratumoral heterogeneity (ITH) of EC has been mentioned but has not been quantitatively measured yet. We aimed to clarify the impact of ITH on pathological diagnosis and P16 methylation, and the concordance between endoscopic biopsy and the corresponding surgically resected tissue.

Methods

We designed a systematic sampling method (SSM) compared with a general sampling method (GSM) to obtain EC tumor tissue, tumor biopsy, and normal squamous epithelium biopsy. MethyLight assay was utilized to test P16 methylation. All specimens obtained by the SSM were pathologically diagnosed.

Results

A total of 81 cases were collected by the GSM, and 91.4% and 8.6% of them were esophageal squamous cell carcinomas (ESCCs) and esophageal adenocarcinomas (EADs), respectively. Nine SSM cases were 100.0% ESCCs. The positive rates of P16 methylation of the GSM tumor and normal tissues were 63.0% (51/81) and 32.1% (26/81), respectively. For SSM samples, tumor tissues were 100.0% (40/40) EC and 85.0% (34/40) P16 methylated; tumor biopsy was 64.4% (29/45) diagnosed of EC and 68.9% P16 methylated; the corresponding normal biopsies were 15.7% (8/51) dysplasia and 54.9% (28/51) P16 methylated. The concordance of pathological diagnosis and P16 methylation between tumor biopsy and the corresponding tumor tissue was 75.0% and 62.5%, respectively.

Conclusion

The SSM we designed was efficient in measuring the ITH of EC. We found inadequate concordance between tumor biopsy and tissue in pathological diagnosis and P16 methylation.

Improving the overall survival prognosis prediction accuracy: A 9-gene signature in CRC patients

Colorectal cancer (CRC) is a malignant tumor and morbidity rates are among the highest in the world. The variation in CRC patients' prognosis prompts an urgent need for new molecular biomarkers to improve the accuracy for predicting the CRC patients' prognosis or as a complement to the traditional TNM staging for clinical practice. CRC patients' gene expression data of HTSeq‐FPKM and matching clinical information were downloaded from The Cancer Genome Atlas (TCGA) datasets. Patients were randomly divided into a training dataset and a test dataset. By univariate and multivariate Cox regression survival analyses and Lasso regression analysis, a prediction model which divided each patient into high‐or low‐risk group was constructed. The differences in survival time between the two groups were compared by the Kaplan–Meier method and the log‐rank test. The weighted gene co‐expression network analysis (WGCNA) was used to explore the relationship between all the survival‐related genes. The survival outcomes of patients whose overall survival (OS) time were significantly lower in the high‐risk group than that in the low‐risk group both in the training and test datasets. Areas under the ROC curves which termed AUC values of our 9‐gene signature achieved 0.823 in the training dataset and 0.806 in the test dataset. A nomogram was constructed for clinical practice when we combined the 9‐gene signature with TNM stage and age to evaluate the survival time of patients with CRC, and the C‐index increased from 0.739 to 0.794. In conclusion, we identified nine novel biomarkers that not only are independent prognostic indexes for CRC patients but also can serve as a good supplement to traditional clinicopathological factors to more accurately evaluate the survival of CRC patients.

Multiregional assessment of CIMP in primary colorectal cancers: Phenotype concordance but marker variability

Intratumor heterogeneity of colorectal cancers (CRCs) is manifested both at the genomic and epigenomic levels. Early genetic aberrations in carcinogenesis are clonal and present throughout the tumors, but less is known about the heterogeneity of the epigenetic CpG island methylator phenotype (CIMP). CIMP characterizes a subgroup of CRCs thought to originate from specific precursor lesions, and it is defined by widespread DNA methylation within promoter regions. In this work, we investigated CIMP in two to four multiregional samples from 30 primary tumors (n = 86 samples) using the consensus Weisenberger gene panel (CACNA1G, IGF2, NEUROG1, RUNX3 and SOCS1). Twenty‐nine of 30 tumors (97%) showed concordant CIMP status in all samples, and percent methylated reference (PMR) values of all five markers had higher intertumor than intratumor variation (P value = 1.5e−09). However, a third of the CIMP+ tumors exhibited discrepancies in methylation status in at least one of the five gene markers. To conclude, CIMP status was consistent within primary CRCs, and it is likely a clonal phenotype. However, spatial discordances of the individual genes suggest that large‐scale analysis of multiregional samples could be of interest for identifying CIMP markers that are robust to intratumor heterogeneity.

What's new?

Colorectal cancers (CRCs) exhibit significant intratumoral genetic and epigenetic heterogeneity. A subgroup of CRCs is characterized in particular by the epigenetic CpG island methylator phenotype (CIMP), though the extent to which CIMP contributes to intratumoral heterogeneity in these tumors is unknown. Here, investigation of CIMP in multiregional samples from primary CRCs shows that CIMP status is highly homogenous within tumors. In one‐third of CIMP‐positive primary CRCs, methylation status differed in at least one of five gene markers investigated. The findings suggest that inclusion of multiregional CRC samples could aid the development of more robust marker panels for CIMP assessment.

Precision Medicine for the Management of Therapy Refractory Colorectal Cancer

In this analysis, we examined the efficacy, feasibility, and limitations of molecular-based targeted therapies in heavily pretreated metastatic colorectal cancer (mCRC) patients after failure of all standard treatments. In this single-center, real-world retrospective analysis of our platform for precision medicine, we mapped the molecular profiles of 60 mCRC patients. Tumor samples of the patients were analyzed using next-generation sequencing panels of mutation hotspots, microsatellite instability testing, and immunohistochemistry. All profiles were reviewed by a multidisciplinary team to provide a targeted treatment recommendation after consensus discussion. In total, we detected 166 mutations in 53 patients. The five most frequently found mutations were TP53, KRAS, APC, PIK3CA, and PTEN. In 28 cases (47% of all patients), a molecularly targeted therapy could be recommended. Eventually, 12 patients (20%) received the recommended therapy. Six patients (10%) had a clinical benefit. The median time to treatment failure was 3.1 months. Our study demonstrates the feasibility and applicability of using targeted therapies in daily clinical practice for heavily pretreated mCRC patients. This could be used as a targeted treatment option in half of the patients.

Intratumor heterogeneity: A new perspective on colorectal cancer research

Colorectal cancers generally consist of multiple subclones. These subclones have their own unique characteristics, resulting in intratumor heterogeneity (ITH). As the discussion of ITH has advanced, a model describing the relationship of ITH to the tumor has gradually emerged. ITH can be divided into two types of intraprimary tumor heterogeneity and intraindividual tumor heterogeneity, the former for further understanding of tumor composition, and the latter for providing more information about evolutionary patterns. With the rapid development of new methods, such as next‐generation, polyguanine region sequencing, and Image detection, researchers may unravel the secrets underlying ITH. The higher the ITH of the tumor, the richer the interaction between the subclones maybe, or the greater the chance of the tumor getting more powerful subclones may be, thus increasing the malignant potential of the tumor. Existing evidence suggests that ITH may increase the ability of tumors to resist treatment and can be used as an independent influence on the prognosis of colorectal cancer. We reviewed 80 recent studies to give researchers a new perspective on colorectal cancer. There is still a limited amount of research in this area. Further study of the relationship between ITH and clinical endpoints may lead to the development of new treatment strategies.

Identifying a ten-microRNA signature as a superior prognosis biomarker in colon adenocarcinoma

Background

Increasing studies have suggested that aberrant expression of microRNAs might play essential roles in the progression of cancers. In this study, we sought to construct a high-specific and superior microRNAs signature to improve the survival prediction of colon adenocarcinoma (COAD) patients.

Methods

The genome-wide miRNAs, mRNA and lncRNA expression profiles and corresponding clinical information of COAD were collected from the TCGA database. Differential expression analysis, Kaplan–Meier curve and time-dependent ROC curve were calculated and performed using R software and GraphPad Prism7. Univariate and multivariate Cox analysis was performed to evaluate the prognostic ability of signature. Functional enrichment analysis was analyzed using STRING database.

Results

We identified ten prognosis-related microRNAs, including seven risky factors (hsa-miR-197, hsa-miR-32, hsa-miR-887, hsa-miR-3199-2, hsa-miR-4999, hsa-miR-561, hsa-miR-210) and three protective factors (hsa-miR-3917, hsa-miR-3189, hsa-miR-6854). The Kaplan–Meier survival analysis showed that the patients with high risk score had shorter overall survival (OS) in test series. And the similar results were observed in both validation and entire series. The time-dependent ROC curve suggested this signature have high accuracy of OS for COAD. The Multivariate Cox regression analysis and stratification analysis suggested that the ten-microRNA signature was an independent factor after being adjusted with other clinical characteristics. In addition, we also found microRNA signature have higher AUC than other signature. Furthermore, we identified some miRNA-target genes that affect lymphatic metastasis and invasion of COAD patients.

Conclusion

In this study, we established a ten-microRNA signature as a potentially reliable and independent biomarker for survival prediction of COAD patients.

Global differences in the prevalence of the CpG island methylator phenotype of colorectal cancer

Background

CpG Island Methylator Phenotype (CIMP) is an epigenetic phenotype in CRC characterized by hypermethylation of CpG islands in promoter regions of tumor suppressor genes, leading to their transcriptional silencing and loss of function. While the prevalence of CRC differs across geographical regions, no studies have compared prevalence of CIMP-High phenotype across regions. The purpose of this project was to compare the prevalence of CIMP across geographical regions after adjusting for variations in methodologies to measure CIMP in a meta-analysis.

Methods

We searched PubMed, Medline, and Embase for articles focusing on CIMP published from 2000 to 2018. Two reviewers independently identified 111 articles to be included in final meta-analysis. We classified methods used to quantify CIMP into 4 categories: a) Classical (MINT marker) Panel group b) Weisenberg-Ogino (W-O) group c) Human Methylation Arrays group and d) Miscellaneous group. We compared the prevalence of CIMP across geographical regions after correcting for methodological variations using meta-regression techniques.

Results

The pooled prevalence of CIMP-High across all studies was 22% (95% confidence interval:21–24%; I² = 94.75%). Pooled prevalence of CIMP-H across Asia, Australia, Europe, North America and South America was 22, 21, 21, 27 and 25%, respectively. Meta-regression analysis identified no significant differences in the prevalence of CIMP-H across geographical regions after correction for methodological variations. In exploratory analysis, we observed variations in CIMP-H prevalence across countries.

Conclusion

Although no differences were found for CIMP-H prevalence across countries, further studies are needed to compare the influence of demographic, lifestyle and environmental factors in relation to the prevalence of CIMP across geographical regions.

Nanogel-mediated delivery of a cocktail of epigenetic drugs plus doxorubicin overcomes drug resistance in breast cancer cells

Epigenetic modifications (e.g., DNA methylation or histone deacetylation) are commonly implicated in cancer chemoresistance. We previously showed that pretreating resistant MCF-7/ADR breast cancer cells with a demethylating agent (5-aza-2'-deoxycytidine (DAC)) or with an inhibitor of histone deacetylase (suberoylanilide hydroxamic acid (SAHA)) sensitized resistant cells to doxorubicin (DOX) treatment. However, even with increasing doses of DOX, a fraction of resistant cells remained nonresponsive to this pretreatment (~ 25% pretreated with DAC, ~ 45% with SAHA). We hypothesized that pretreating resistant cells with a combination of epigenetic drugs (DAC + SAHA) could more effectively overcome drug resistance. We postulated that delivery of epigenetic drugs encapsulated in biodegradable nanogels (NGs) would further enhance their efficacy. MCF-7/ADR cells were first treated with a single drug vs. a combination of epigenetic drugs, either as solutions or encapsulated in NGs, then subjected to DOX, either in solution or in NGs. Antiproliferative data showed that pretreatment with epigenetic drugs in NGs, then with DOX in NGs, was most effective in overcoming resistance; this treatment inhibited cell growth by > 90%, even at low doses of DOX. Cell cycle analysis showed that a major fraction of cells treated with a cocktail of epigenetic drugs + DOX, all in NG formulations, remained in the G2/M cell cycle arrest phase for a prolonged period. The mechanism of better efficacy of epigenetic drugs in NGs could be attributed to their sustained effect. A similar strategy could be developed for other cancer cells in which drug resistance is due to epigenetic modifications.

Heterogeneity in Colorectal Cancer: A Challenge for Personalized Medicine?

High inter-patient variability and high spatial heterogeneity are features of colorectal cancer (CRC). This may influence the molecular characterization of tumor tissue, now mandatory for patients with metastatic CRC who are candidates for treatment with an anti-EGFR mAb, as false-negative results can occur, leading to non optimal therapy. Moreover, temporal molecular heterogeneity during treatment is known to influence the response to therapy and prognosis. We present a literature overview of advances made in characterizing molecular heterogeneity in CRC, underlining that the analysis of liquid biopsy could represent an efficient non-invasive tool to overcome the problem. We believe that understanding CRC heterogeneity is fundamental for a more accurate diagnosis, for selecting the best targets to ensure prolonged antitumor response, and for monitoring minimal residual disease and the onset of resistance to therapy, all essential components of successful personalized treatment.

Impact of Global DNA Methylation in Treatment Outcome of Colorectal Cancer Patients

Background: Global DNA methylation has an impact in cancer pathogenesis and progression. This study aimed at investigating the impact of global DNA methylation in treatment outcome of Colorectal Cancer (CRC).

Patients and Methods: Global DNA methylation was measured by LC/MS/MS in peripheral blood leucocytes of 102, 48, and 32 Egyptian CRC patients at baseline and after 3 and 6 months of Fluoropyrimidine (FP) therapy respectively, in addition to 32 normal healthy matched in age and sex. The genetic expressions of DNA methyl transferases (DNMTs) were determined and correlated with patients‘ survival using univariate and multivariate methods of analyses.

Results: Egyptian CRC patients had significant global hypomethylation of 5mC level and 5mC % with overexpression of DNMT3A and DNMT3B. Significant higher 5mC levels were shown in patients > 45 years, male gender, T2 tumors, stage II, negative lymph nodes, and absence of metastasis. FP therapy significantly reduced DNA methylation particularly in the subgroups of patients with high DNA methylation level at baseline and good prognostic features. After 3 years of follow up, patients with 5mC % > 8.02% had significant poor overall survival (OS) while, significant better event-free survival (EFS) was found in patients with 5mC level > 0.55. High initial CEA level and presence of metastasis were significantly associated with hazards of disease progression and death.

Conclusion: Global DNA methylation has a significant impact on the treatment outcome and survival of Egyptian CRC patients treated with FP- based therapy.

Optimal detection of clinically relevant mutations in colorectal carcinoma: sample pooling overcomes intra-tumoral heterogeneity

Intra-tumoral genomic heterogeneity is a well-established biologic property of human malignancies with emerging roles in cancer progression and therapy resistance. However, its impact on the clinical utility of genomic testing in patient management remains unclear. Furthermore, best practices to account for heterogeneity in the provision of highly accurate, clinically valid molecular testing have yet to be firmly established. Genomic biomarkers for the management of colorectal carcinoma are both well-established (ie, KRAS, NRAS) and emerging (BRAF, PIK3CA, and others) in respect to therapy selection and clinical trial eligibility. Critically, standard colorectal carcinoma management requires the exclusion of KRAS and NRAS mutations; thus optimal procedures to control for potential intra-tumoral heterogeneity are clinically important. Here, we assessed heterogeneity among three intra-tumoral sites within 99 colorectal carcinomas cases on a CLIA-validated oncology next generation sequencing assay and examined whether a pooling strategy overcame any discordant results. Overall, 11% of cases demonstrated discordant mutation results between sites; 2% of cases were discrepant for mutations within RAS genes while the remainder was discrepant in PIK3CA. Half of the discrepant cases were associated with borderline tumor cellularity assessment. Further, a sample pooling strategy across all three sites successfully detected the relevant mutation in all but one case. Our results indicate that intra-tumoral genomic heterogeneity of clinically relevant genes within colorectal carcinoma is a relatively infrequent occurrence and that a simple strategy to pool DNA from several tumor sites with adequate cellularity minimizes the risk of false negative results even further to ensure optimal patient management.