Oxaliplatin and infliximab synergize to induce regression of colon cancer

Longitudinal single-cell RNA-seq analysis reveals stress-promoted chemoresistance in metastatic ovarian cancer

Chemotherapy resistance is a critical contributor to cancer mortality and thus an urgent unmet challenge in oncology. To characterize chemotherapy resistance processes in high-grade serous ovarian cancer, we prospectively collected tissue samples before and after chemotherapy and analyzed their transcriptomic profiles at a single-cell resolution. After removing patient-specific signals by a novel analysis approach, PRIMUS, we found a consistent increase in stress-associated cell state during chemotherapy, which was validated by RNA in situ hybridization and bulk RNA sequencing. The stress-associated state exists before chemotherapy, is subclonally enriched during the treatment, and associates with poor progression-free survival. Co-occurrence with an inflammatory cancer-associated fibroblast subtype in tumors implies that chemotherapy is associated with stress response in both cancer cells and stroma, driving a paracrine feed-forward loop. In summary, we have found a resistant state that integrates stromal signaling and subclonal evolution and offers targets to overcome chemotherapy resistance.

COVID-19 and cancer: start the resolution!

Coronavirus disease 2019 (COVID-19) due to infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been an ongoing pandemic causing significant morbidity and mortality worldwide. The “cytokine storm” is a critical driving force in severe COVID-19 cases, leading to hyperinflammation, multi-system organ failure, and death. A paradigm shift is emerging in our understanding of the resolution of inflammation from a passive course to an active biochemical process driven by endogenous specialized pro-resolving mediators (SPMs), such as resolvins, protectins, lipoxins, and maresins. SPMs stimulate macrophage-mediated debris clearance and counter pro-inflammatory cytokine production, a process collectively termed as the “resolution of inflammation.” Hyperinflammation is not unique to COVID-19 and also occurs in neoplastic conditions, putting individuals with underlying health conditions such as cancer at elevated risk of severe SARS-CoV-2 infection. Despite approaches to block systemic inflammation, there are no current therapies designed to stimulate the resolution of inflammation in patients with COVID-19 or cancer. A non-immunosuppressive therapeutic approach that reduces the cytokine storm in patients with COVID-19 and cancer is urgently needed. SPMs are potent immunoresolvent and organ-protective lipid autacoids that stimulate the resolution of inflammation, facilitate clearance of infections, reduce thrombus burden, and promote a return to tissue homeostasis. Targeting endogenous lipid mediators, such as SPMs, offers an entirely novel approach to control SARS-CoV-2 infection and cancer by increasing the body’s natural reserve of pro-resolving mediators without overt toxicity or immunosuppression.

A New Oxaliplatin Resistance-Related Gene Signature With Strong Predicting Ability in Colon Cancer Identified by Comprehensive Profiling

Numerous colon cancer cases are resistant to chemotherapy based on oxaliplatin and suffer from relapse. A number of survival- and prognosis-related biomarkers have been identified based on database mining for patients who develop drug resistance, but the single individual gene biomarker cannot attain high specificity and sensitivity in prognosis prediction. This work was conducted aiming to establish a new gene signature using oxaliplatin resistance-related genes to predict the prognosis for colon cancer. To this end, we downloaded gene expression profile data of cell lines that are resistant and not resistant to oxaliplatin from the Gene Expression Omnibus (GEO) database. Altogether, 495 oxaliplatin resistance-related genes were searched by weighted gene co-expression network analysis (WGCNA) and differential expression analysis. As suggested by functional analysis, the above genes were mostly enriched into cell adhesion and immune processes. Besides, a signature was built based on four oxaliplatin resistance-related genes selected from the training set to predict the overall survival (OS) by stepwise regression and least absolute shrinkage and selection operator (LASSO) Cox analysis. Relative to the low risk score group, the high risk score group had dismal OS (P < 0.0001). Moreover, the area under the curve (AUC) value regarding the 5-year OS was 0.72, indicating that the risk score was accurate in the prediction of OS for colon cancer patients (AUC >0.7). Additionally, multivariate Cox regression suggested that the signature constructed based on four oxaliplatin resistance-related genes predicted the prognosis for colon cancer cases [hazard ratio (HR), 2.77; 95% CI, 2.03–3.78; P < 0.001]. Finally, external test sets were utilized to further validate the stability and accuracy of oxaliplatin resistance-related gene signature for prognosis of colon cancer patients. To sum up, this study establishes a signature based on four oxaliplatin resistance-related genes for predicting the survival of colon cancer patients, which sheds more light on the mechanisms of oxaliplatin resistance and helps identify colon cancer cases with a dismal prognostic outcome.