Mismatch Repair Status Correlates with Survival in Young Adults with Metastatic Colorectal Cancer

Discovering predisposing genes for hereditary breast cancer using deep learning

Breast cancer (BC) is the most common malignancy affecting Western women today. It is estimated that as many as 10% of BC cases can be attributed to germline variants. However, the genetic basis of the majority of familial BC cases has yet to be identified. Discovering predisposing genes contributing to familial BC is challenging due to their presumed rarity, low penetrance, and complex biological mechanisms. Here, we focused on an analysis of rare missense variants in a cohort of 12 families of Middle Eastern origins characterized by a high incidence of BC cases. We devised a novel, high-throughput, variant analysis pipeline adapted for family studies, which aims to analyze variants at the protein level by employing state-of-the-art machine learning models and three-dimensional protein structural analysis. Using our pipeline, we analyzed 1218 rare missense variants that are shared between affected family members and classified 80 genes as candidate pathogenic. Among these genes, we found significant functional enrichment in peroxisomal and mitochondrial biological pathways which segregated across seven families in the study and covered diverse ethnic groups. We present multiple evidence that peroxisomal and mitochondrial pathways play an important, yet underappreciated, role in both germline BC predisposition and BC survival.

Survival outcome and prognostic factors for early-onset and late-onset metastatic colorectal cancer: a population based study from SEER database

Colorectal cancer is the third most common cancer worldwide and there has been a concerning increase in the incidence rate of colorectal cancer among individuals under the age of 50. This study compared the survival outcome between early-onset and late-onset metastatic colorectal cancer to find the differences and identify their prognostic factors. We obtained patient data from SEER database. Survival outcome was estimated using Kaplan-Meier survival curves and compared using the log-rank test. Univariate and multivariate analyses were conducted utilizing COX models to identify their independent prognostic factors. A total of 10,036 early-onset metastatic colorectal (EOCRC) cancer patients and 56,225 late-onset metastatic colorectal cancer (LOCRC) patients between 2010 and 2019 were included in this study. EOCRC has more survival benefits than LOCRC. Tumor primary location (p < 0.001), the location of metastasis (p < 0.001) and treatment modalities (p < 0.001) affect the survival outcomes between these two groups of patients. Female patients had better survival outcomes in EOCRC group (p < 0.001), but no difference was found in LOCRC group (p = 0.57). In conclusion, our study demonstrated that EOCRC patients have longer survival time than LOCRC patients. The sex differences in survival of metastatic colorectal cancer patients are associated with patients' age. These findings contribute to a better understanding of the differences between metastatic EOCRC and LOCRC, and can help inform the development of more precise treatment guidelines to improve prognosis.

KEYSTEP-008: phase II trial of pembrolizumab-based combination in MSI-H/dMMR metastatic colorectal cancer

Robust clinical activity has been observed with the immune checkpoint inhibitor pembrolizumab in patients with microsatellite instability-high/mismatch repair-deficient (MSI-H/dMMR) metastatic colorectal cancer (mCRC). However, given the response rate of 45% and a median progression-free survival of 16.5 months with first-line pembrolizumab demonstrated in KEYNOTE-177, there is room for improvement. Targeting a second immune receptor, such as CTLA-4, LAG-3, TIGIT, or ILT-4 may improve efficacy of PD-1 inhibition. Here we describe the design and rationale for the open-label, randomized, phase II KEYSTEP-008 trial, which will evaluate the efficacy and safety of pembrolizumab-based combination therapy compared with pembrolizumab monotherapy in chemotherapy-refractory (cohort A) or previously untreated (cohort B) MSI-H/dMMR mCRC. Clinical Trial Registration: NCT04895722 (ClinicalTrials.gov).

Early Onset Metastatic Colorectal Cancer: Current Insights and Clinical Management of a Rising Condition

Despite a recent overall decrease in colorectal cancer (CRC) incidence and mortality, there has been a significant rise in CRC diagnoses in young adults. Early onset colorectal cancer (EOCRC) is defined as CRC diagnosed before the age of 50. Possible predisposing conditions include not only genetic syndromes but also other risk factors, such as microbiome alteration, antibiotic exposure, obesity, diabetes mellitus, and inflammatory bowel disease. EOCRC tends to be diagnosed later than in the older counterpart because of a lack of awareness and the fact that screening for CRC usually starts at the age of 50. Furthermore, CRC in young adults seems to be related to unique molecular features and more aggressive clinical behavior. This paper aims to provide an in-depth review of this poorly understood subject, with a comprehensive review of the state of the art and considerations for future perspectives.

A novel nomogram based on cell cycle-related genes for predicting overall survival in early-onset colorectal cancer

BACKGROUND

Although the incidence of late-onset colorectal cancer (LOCRC) has decreased, the incidence of early-onset colorectal cancer (EOCRC) is still rising dramatically. Heterogeneity in the genomic, biological, and clinicopathological characteristics between EOCRC and LOCRC has been revealed. Therefore, the previous prognostic models based on the total CRC patient population might not be suitable for EOCRC patients. Here, we constructed a prognostic classifier to enhance the precision of individualized treatment and management of EOCRC patients.

METHODS

EOCRC expression data were downloaded from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. The regulatory pathways were explored by gene set enrichment analysis (GSEA). The prognostic model was developed by univariate Cox-LASSO-multivariate Cox regression analyses of GEO samples. TCGA samples were used to verify the model. The expression and mutation profiles and immune landscape of the high-risk and low-risk cohorts were analyzed and compared. Finally, the expression and prognostic value of the model genes were verified by immunohistochemistry and qRT‒PCR analysis.

RESULTS

The cell cycle was identified as the most significantly enriched oncological signature of EOCRC. Then, a 4-gene prognostic signature comprising MCM2, INHBA, CGREF1, and KLF9 was constructed. The risk score was an independent predictor of overall survival. The area under the curve values of the classifier for 1-, 3-, and 5-year survival were 0.856, 0.893, and 0.826, respectively, in the training set and 0.749, 0.858, and 0.865, respectively, in the validation set. Impaired DNA damage repair capability (p < 0.05) and frequent PIK3CA mutations (p < 0.05) were found in the high-risk cohort. CD8 T cells (p < 0.05), activated memory CD4 T cells (p < 0.01), and activated dendritic cells (p < 0.05) were clustered in the low-risk group. Finally, we verified the expression of MCM2, INHBA, CGREF1, and KLF9. Their prognostic value was closely related to age.

CONCLUSION

In this study, a robust prognostic classifier for EOCRC was established and validated. The findings may provide a reference for individualized treatment and medical decision-making for patients with EOCRC.

Tumor Biomarker Testing for Metastatic Colorectal Cancer: a Canadian Consensus Practice Guideline

The systemic therapy management of metastatic colorectal cancer (mCRC) has evolved from primarily cytotoxic chemotherapies to now include targeted agents given alone or in combination with chemotherapy, and immune checkpoint inhibitors. A better understanding of the pathogenesis and molecular drivers of colorectal cancer not only aided the development of novel targeted therapies but led to the discovery of tumor mutations which act as predictive biomarkers for therapeutic response. Mutational status of the KRAS gene became the first genomic biomarker to be established as part of standard of care molecular testing, where KRAS mutations within exons 2, 3, and 4 predict a lack of response to anti- epidermal growth factor receptor therapies. Since then, several other biomarkers have become relevant to inform mCRC treatment; however, there are no published Canadian guidelines which reflect the current standards for biomarker testing. This guideline was developed by a pan-Canadian advisory group to provide contemporary, evidence-based recommendations on the minimum acceptable standards for biomarker testing in mCRC, and to describe additional biomarkers for consideration.

Development of novel models for predicting mismatch repair protein deficiency and relevant disease-free survival in colorectal cancer patients

PURPOSE

DNA mismatch repair (MMR) protein deficiency has attached more attention for its potential to be a biomarker of immunotherapy for colorectal cancer (CRC) patients. However, clinical models involving the expression status of MMR protein are rare. Herein, we sought to develop two clinical models (a diagnostic model for the prediction of MMR status and a prognostic model for the prediction of disease-free survival) for CRC patients.

METHODS

A total of 582 CRC patients were finally included. There were 53 patients with deficient expression of MMR protein. The differences between the deficient MMR (dMMR) group and the proficient MMR (pMMR) group were analyzed.

RESULTS

Compared to pMMR patients, those with dMMR status were younger and had better pathological features (depth of invasion, lymph node metastasis, distant metastasis, pathological stage, perineuronal invasion, and PLT level) and disease-free survival (DFS). The tumor location of the left colon, adenocarcinoma, and abnormal PLT level were identified as the independent predictors for pMMR. Based on these data, we developed the diagnostic model using Logistic regression analysis. It showed a satisfactory accuracy (AUC = 82.3% in the derivate set; AUC = 73.6% in the validation set). Furthermore, pMMR, poorer differentiation, perineuronal invasion, distant metastasis, lower hemoglobin level, and abnormal CEA level were established as the independent prognostic factors of poorer DFS. Based on them, a prognostic model with valuable performance (1-year AUC = 75.5%/3-year AUC = 76.9% in the derivate set; 1-year AUC = 72.3%/3-year AUC = 73.8% in the validation set) was developed.

CONCLUSIONS

Our diagnostic and prognostic models could identify CRC patients at risk for pMMR protein expression and disease recurrence. It may contribute to improving the diagnosis and treatment of CRC patients at an individual level.