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Background To develop a radiomics signature for predicting overall survival (OS)/progression-free survival (PFS) in patients with medulloblastoma (MB), and to investigate the incremental prognostic value and biological pathways of the radiomics patterns. Methods A radiomics signature was constructed based on magnetic resonance imaging (MRI) from a training cohort (n = 83), and evaluated on a testing cohort (n = 83). Key pathways associated with the signature were identified by RNA-seq (GSE151519). Prognostic value of pathway genes was assessed in a public GSE85218 cohort. Findings The radiomics-clinicomolecular signature predicted OS (C-index 0.762) and PFS (C-index 0.697) better than either the radiomics signature (C-index: OS: 0.649; PFS: 0.593) or the clinicomolecular signature (C-index: OS: 0.725; PFS: 0.691) alone, with a better calibration and classification accuracy (net reclassification improvement: OS: 0.298, P = 0.022; PFS: 0.252, P = 0.026). Nine pathways were significantly correlated with the radiomics signature. Average expression value of pathway genes achieved significant risk stratification in GSE85218 cohort (log-rank P = 0.016). Interpretation This study demonstrated radiomics signature, which associated with dysregulated pathways, was an independent parameter conferring incremental value over clinicomolecular factors in survival predictions for MB patients. Funding A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Background Pancreatic cancer (PC) is one of the most lethal solid malignancies in the world due to its excessive cell proliferation and aggressive metastatic features. Emerging evidences revealed the importance of posttranscriptional modifications of RNAs in PC progression. However, knowledge about the 5-methylcytosine (m5C) RNA modification in PC is still extremely limited. In this study, we attempted to explore the expression changes and clinical significances of 12 known m5C-related genes among PC patients. Methods A total of 362 normal and 382 tumor specimens from PC patients were examined for candidate m5C-related gene and protein expression by using quantitative PCR (qPCR) and immunohistochemistry (IHC). The proliferation rate of PC cells was detected by MTS assay. Xenograft mouse models were used to assess the role of NSUN6 in PC tumor formation. Findings Through analyzing the four Gene Expression Omnibus (GEO) databases, six m5C-related genes shown significant and consistent alterations were selected for further examination in our 3 independent PC cohorts. Finally, we identified the reduction of NSUN6 as a common feature of all PC sample sets examined. NSUN6 expression correlated with clinicopathologic parameters including T stage, and Ki67+ cell rate. Further assessing the transcriptional profiles of 50 PC tissues, we found biological processes associated with cell proliferation like cell cycle and G2M checkpoint were enriched in NSUN6 lower expression group. Helped by in vitro PC cell lines and in vivo xenograft mouse models, we confirmed the role of NSUN6 in regulating cell proliferation and PC tumor growth. Last but also importantly, we also show the good performance of NSUN6 in evaluating tumor recurrence and survival among PC patients. Interpretation Our data suggested that NSUN6 is an important factor involved in regulating cell proliferation of PC, and highlights the potential of novel m5C-based clinical modalities as a therapeutic approach in PC patients. Funding This study was supported by the National Natural Science Foundation of China (Grant Nos. 81803014, 81802424, and 81802911).

Background/Objectives: Tumour budding and poorly differentiated clusters (PDC) represent forms of tumour invasion. We hypothesised that T-cell densities (reflecting adaptive anti-tumour immunity) might be inversely associated with tumour budding and PDC in colorectal carcinoma. Methods: Utilising 915 colon and rectal carcinomas in two U.S.-wide prospective cohort studies, and multiplex immunofluorescence combined with machine learning algorithms, we assessed CD3, CD4, CD8, CD45RO (PTPRC), and FOXP3 co-expression patterns in lymphocytes. Tumour budding and PDC at invasive fronts were quantified by digital pathology and image analysis using the International tumour Budding Consensus Conference criteria. Using covariate data of 4,420 incident colorectal cancer cases, inverse probability weighting (IPW) was integrated with multivariable logistic regression analysis that assessed the association of T-cell subset densities with tumour budding and PDC while adjusting for selection bias due to tissue availability and potential confounders, including microsatellite instability status. Findings: Tumour budding counts were inversely associated with density of CD3+CD8+ [lowest vs. highest: multivariable odds ratio (OR), 0.50; 95% confidence interval (CI), 0.35–0.70; Ptrend < 0.001] and CD3+CD8+CD45RO+ cells (lowest vs. highest: multivariable OR, 0.44; 95% CI, 0.31–0.63; Ptrend < 0.001) in tumour epithelial region. Tumour budding levels were associated with higher colorectal cancer-specific mortality (multivariable hazard ratio, 2.13; 95% CI, 1.57–2.89; Ptrend < 0.001) in Cox regression analysis. There were no significant associations of PDC with T-cell subsets. Interpretation: Tumour epithelial naïve and memory cytotoxic T cell densities are inversely associated with tumour budding at invasive fronts, suggesting that cytotoxic anti-tumour immunity suppresses tumour microinvasion.

Background Emerging evidence indicates that small nucleolar RNAs (snoRNAs) play a central role in oncogenesis. Herein, we systematically evaluated expression profiles of snoRNAs in colorectal cancer (CRC) and investigated their clinical and functional role in this malignancy. Methods We compared expression levels of snoRNAs between cancer and normal tissues using publicly available datasets and identified the most differentially expressed and commonly upregulated snoRNAs in CRC. These results were examined in 489 colorectal tissues to assess their clinical significance, followed by a series of in vitro and in vivo experiments to evaluate the functional role of candidate snoRNAs. Results Using multiple RNA profiling datasets, we identified consistent overexpression of SNORA21 in CRC. In the clinical validation cohorts, the expression level of SNORA21 was upregulated in colorectal adenomas and cancers. Furthermore, elevated SNORA21 emerged as an independent factor for predicting poor survival. Both in vitro and in vivo experiments revealed that CRISPR/Cas9-mediated inhibition of SNORA21 expression resulted in decreased cell proliferation and invasion through modulation of multiple cancer related pathways. Conclusions We systematically identified SNORA21 as a key oncogenic snoRNA in CRC, which plays an important role in cancer progression, and might serve as an important prognostic biomarker in CRC., Highlights • Systematic and comprehensive analysis revealed that SNORA21 was significantly upregulated in CRC. • Elevated SNONA21 expression was related to metastasis and predicted poor prognosis in CRC patients. • SNORA21 is a promising cancer prognostic biomarker and a potential therapeutic target in CRC. Emerging evidence indicates that small nucleolar RNAs (snoRNAs) might play a central role in oncogenesis; however, the clinical significance and functional roles of snoRNAs in colorectal cancer (CRC) remain unclear. Herein, using multiple publicly available datasets, we systematically assessed expression profiles of snoRNAs in CRC and elucidated that the high expression of SNORA21 was associated with distant metastasis and poor overall survival. A series of in vitro and in vivo experiments revealed oncogenic role for SNORA21. Our findings indicate that SNORA21 is a promising cancer prognostic biomarker and a potential therapeutic target in CRC.

Epidermal growth factor receptor (EGFR) mutations have been used as the strongest predictor of effectiveness of treatment with EGFR tyrosine kinase inhibitors (TKIs). Three most common EGFR mutations (L858R, exon 19 deletion, and T790M) are known to be major selection markers for EGFR-TKIs therapy. Here, we developed a multiplex picodroplet digital PCR (ddPCR) assay to detect 3 common EGFR mutations in 1 reaction. Serial-dilution experiments with genomic DNA harboring EGFR mutations revealed linear performance, with analytical sensitivity ~ 0.01% for each mutation. All 33 EGFR-activating mutations detected in formalin-fixed paraffin-embedded (FFPE) tissue samples by the conventional method were also detected by this multiplex assay. Owing to the higher sensitivity, an additional mutation (T790M; including an ultra-low-level mutation, Highlights • An ultrasensitive multiplex picodroplet digital PCR (ddPCR) assay to detect 3 common EGFR mutations in 1 reaction was developed. • This multiplex mutation detection of common mutations of EGFR is a feasible alternative. • A rare pretreatment EGFR mutation (T790M) with a mutant allele frequency below 0.1% was detected via this multiplex assay. Three most common EGFR mutations (L858R, exon 19 deletion, and T790M) are known to be major selection markers for EGFR-TKI therapy. In this article, we developed a multiplex picodroplet digital PCR (ddPCR) assay to detect 3 common EGFR mutations in 1 reaction with 0.01% sensitivity. All 33 EGFR-activating mutations detected in FFPE samples by the conventional method were also detected by this multiplex assay. Owing to the higher sensitivity, an additional mutation was detected in the same reaction. Results of this proof-of-principle study on clinical samples indicate clinical utility of multiplex ddPCR for screening for multiple EGFR mutations.

We investigated the hypothesis that the varying treatment efficacy of adjuvant 5-fluorouracil (5FU) in stage III colon cancer is linked to the TP53 mutational status. ABCSG-90 was a prospective randomized trial in which effect of adjuvant 5FU was studied in stage III colon cancer patients. Tumor material of 70% of these patients (389/572) was available for analysis of the biomarker TP53 using a TP53-gene-specific Sanger sequencing protocol. Median follow-up was 88 months. TP53 mutation frequency was 33%. A significant interaction between TP53 status, outcomes and nodal category was found (P = 0.0095). In the N1 category, TP53 wildtype patients had significantly better overall survival than TP53 mutated (81.0% vs. 62.0% overall survival at 5 years; HR = 2.131; 95% CI: 1.344–3.378; P = 0.0010). In the N2 category, the TP53 status did not affect survival (P = 0.4992). In TP53 wildtype patients, the prognostic significance of N category was significantly enhanced (P = 0.0002). In TP53 mutated patients, survival curves of N1 and N2 patients overlapped and nodal category was no longer prognostic. The biomarker TP53 independently predicted effect of adjuvant 5FU in N1 colon cancer patients. TP53 was not predictive in N2 patients, in whom 5FU is known to have no effect., Highlights • The TP53 status was found to be an independent predictive marker for the effect of adjuvant 5FU in stage III colon cancer. • In the N1 category, patients with wildtype TP53 experienced a significant survival benefit from adjuvant 5FU. • In TP53 mutant patients survival curves of N1 and N2 patients overlapped and nodal category was no longer prognostic. Postoperative chemotherapy is recommended for all patients with lymph node positive colon cancer. In colon cancer, mutations in the TP53 gene are present in more than 30% of tumors. We found that the most commonly used postoperative chemotherapy resulted in a marked survival benefit for patients with normal TP53 status while it was associated with significant survival disadvantage in TP53 mutant patients. Overall the survival disadvantage of the mutated patients almost balanced the survival benefit of the TP53 normal patients. This might be an explanation why chemotherapy resulted in less progress in survival of colon cancer than we would have expected.

The overall 5-year survival for melanoma is 91%. However, if distant metastasis occurs (stage IV), cure rates are, Highlights • A seven-miRNA panel (MELmiR-7) detected the presence of melanoma with high sensitivity (93%) and specificity (≥ 82%). • In serially collected stage IV specimens, members of the ‘MELmiR-7’ panel confirmed tumour progression in 100% of cases. • The ‘MELmiR-7’ panel is superior to currently used serological markers for melanoma progression, recurrence, and survival.

Highlights • Biology-driven strategy can be used in development of prognostic model. • The BCSC-associated miRNA classifier can predict prognosis for HR + HER2 − breast cancer. • The BCSC-associated miRNA classifier outperforms IHC4 scoring and 21-gene RS. • Chemotherapy can improve DRFS in patients predicted as high-risk. Breast cancer patients with high proportion of cancer stem cells (BCSCs) have poor clinical outcomes. MiRNAs regulate key features of BCSCs as oncogenes or tumor suppressors. Although hormone receptor (HR)-positive, HER2-negative breast cancers are the most common subtype, current methods are inadequate to predict its clinical outcome. In this multicenter study, we identified and validated a 10 BCSC-associated-miRNA classifier that can predict survival for HR + HER2 − patients. Retrospective analysis showed that this classifier outperformed IHC4 scoring and 21-gene Recurrence Score (RS), and chemotherapy could improve survival in high-risk patients determined by this classifier. This model may facilitate personalized clinical decision for HR + HER2 − individuals., Purpose Breast cancer patients with high proportion of cancer stem cells (BCSCs) have unfavorable clinical outcomes. MicroRNAs (miRNAs) regulate key features of BCSCs. We hypothesized that a biology-driven model based on BCSC-associated miRNAs could predict prognosis for the most common subtype, hormone receptor (HR)-positive, HER2-negative breast cancer patients. Patients and Methods After screening candidate miRNAs based on literature review and a pilot study, we built a miRNA-based classifier using LASSO Cox regression method in the training group (n = 202) and validated its prognostic accuracy in an internal (n = 101) and two external validation groups (n = 308). Results In this multicenter study, a 10-miRNA classifier incorporating miR-21, miR-30c, miR-181a, miR-181c, miR-125b, miR-7, miR-200a, miR-135b, miR-22 and miR-200c was developed to predict distant relapse free survival (DRFS). With this classifier, HR + HER2 − patients were scored and classified into high-risk and low-risk disease recurrence, which was significantly associated with 5-year DRFS of the patients. Moreover, this classifier outperformed traditional clinicopathological risk factors, IHC4 scoring and 21-gene Recurrence Score (RS). The patients with high-risk recurrence determined by this classifier benefit more from chemotherapy. Conclusions Our 10-miRNA-based classifier provides a reliable prognostic model for disease recurrence in HR + HER2 − breast cancer patients. This model may facilitate personalized therapy-decision making for HR + HER2 − individuals.