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Abstract Background In the last years, several efforts have been made to classify colorectal cancer (CRC) into well-defined molecular subgroups, representing the intrinsic inter-patient heterogeneity, known as Consensus Molecular Subtypes (CMSs). Methods In this work, we performed a meta-analysis of CRC patients stratified into four CMSs. We identified a negative correlation between a high level of anaplastic lymphoma kinase (ALK) expression and relapse-free survival, exclusively in CMS1 subtype. Stemming from this observation, we tested cell lines, patient-derived organoids and mice with potent ALK inhibitors, already approved for clinical use. Results ALK interception strongly inhibits cell proliferation already at nanomolar doses, specifically in CMS1 cell lines, while no effect was found in CMS2/3/4 groups. Furthermore, in vivo imaging identified a role for ALK in the dynamic formation of 3D tumor spheroids. Consistently, ALK appeares constitutively phosphorylated in CMS1, and it signals mainly through the AKT axis. Mechanistically, we found that CMS1 cells display several copies of ALKAL2 ligand and ALK-mRNAs, suggesting an autocrine loop mediated by ALKAL2 in the activation of ALK pathway, responsible for the invasive phenotype. Consequently, disruption of ALK axis mediates the pro-apoptotic action of CMS1 cell lines, both in 2D and 3D and enhanced cell-cell adhesion and e-cadherin organization. In agreement with all these findings, the ALK signature encompassing 65 genes statistically associated with worse relapse-free survival in CMS1 subtype. Finally, as a proof of concept, the efficacy of ALK inhibition was demonstrated in both patient-derived organoids and in tumor xenografts in vivo. Conclusions Collectively, these findings suggest that ALK targeting may represent an attractive therapy for CRC, and CMS classification may provide a useful tool to identify patients who could benefit from this treatment. These findings offer rationale and pharmacological strategies for the treatment of CMS1 CRC.

Metastasis is responsible for the majority of cancer‐related deaths. Particularly, challenging is the management of metastatic cancer of unknown primary site (CUP), whose tissue of origin (TOO) remains undetermined even after extensive investigations and whose therapy is rather unspecific and poorly effective. Molecular approaches to identify the most probable TOO of CUPs can overcome some of these issues. In this study, we applied a predetermined set of 89 microRNAs (miRNAs) to infer the TOO of 53 metastatic cancers of unknown or uncertain origin. The miRNA expression was assessed with droplet digital PCR in 159 samples, including primary tumors from 17 tumor classes (reference set) and metastases of known and unknown origin (test set). We combined two different statistical models for class prediction to obtain the most probable TOOs: the nearest shrunken centroids approach of Prediction Analysis of Microarrays (PAMR) and the least absolute shrinkage and selection operator (LASSO) models. The molecular test was successful for all formalin‐fixed paraffin‐embedded samples and provided a TOO identification within 1 week from the biopsy procedure. The most frequently predicted origins were gastrointestinal, pancreas, breast, lung, and bile duct. The assay was applied also to multiple metastases from the same CUP, collected from different metastatic sites: The predictions showed a strong agreement, intrinsically validating our assay. The final CUPs' TOO prediction was compared with the clinicopathological hypothesis of primary site. Moreover, a panel of 13 miRNAs proved to have prognostic value and be associated with overall survival in CUP patients. Our study demonstrated that miRNA expression profiling in CUP samples could be employed as diagnostic and prognostic test. Our molecular analysis can be performed on request, concomitantly with standard diagnostic workup and in association with genetic profiling, to offer valuable indications about the possible primary site, thereby supporting treatment decisions.

Background: Programmed cell death 1 (PD-1) and PD-ligand 1 (PD-L1) inhibitors represent novel therapeutic options for advanced non-small cell lung cancer (NSCLC). However, approximately 50% of patients do not benefit from therapy and experience rapid disease progression. PD-L1 expression is the only approved biomarker of benefit to anti-PD-1/PD-L1 therapy. However, its weakness has been evidenced in many studies. More recently, tumor mutational burden (TMB) has proved to be a suitable biomarker, but its calculation is difficult to obtain for all patients. Methods: We tested specific NSCLC genetic alterations as potential immunotherapy biomarkers. Tumor DNA was obtained from advanced NSCLC patients treated with anti-PD-1 monoclonal antibody nivolumab ( n = 44) or pembrolizumab ( n = 3). The mutational status of 22 genes was assessed by targeted next-generation sequencing and the association with survival was tested in uni- and multivariate models. The association between gene mutations and clinical benefit was also investigated. Results: The most frequently mutated genes were TP53 (49%), KRAS (43%), ERBB2 (13%), SMAD4 (13%), DDR2 (13%), STK11 (9%), ERBB4 (6%), EGFR (6%), BRAF (6%), and MET (6%). We confirmed that KRAS mut patients have a better response to PD-1 inhibitors, showing a longer progression-free survival (PFS) and overall survival (OS) than KRAS wt patients. In addition, we observed that patients with ERBB -family mutations, including EGFR, ERBB2 , and ERBB4 all failed to respond to PD-1 antibodies, independently of KRAS status. Conclusions: This study suggests that the analysis of KRAS and ERBB -family gene mutational status is valuable when assessing the clinical practice for the selection of NSCLC patients to treat with PD-1 inhibitors.

Archival formalin-fixed paraffin-embedded (FFPE) tissues represent an extraordinary source of smallRNAs, including microRNAs (miRNAs). Contrary to other RNA molecules, miRNAs are stable, nuclease-resistant and quantifiable even in low quality samples. The accurate assessment of miRNA levels in archival samples is of great interest for many pathological conditions, including cancer. In human tumors, microRNA expression is type-specific and can be used as diagnostic, prognostic or response-to-treatment biomarker. In this study, we provide a method for multiple miRNA quantification in 96-well plates, using EvaGreen-based droplet digital PCR technology and miRCURY LNA miRNA assays. This approach allows the absolute quantification of a customizable panel of miRNAs at the same time and under identical experimental conditions, to be used for diagnostic or prognostic applications.