Background: Potential prognostic biomarker candidates for hepatocellular carcinoma (HCC) are abundant, but their generalizability is unexplored. We cross-validated markers of overall survival (OS) and vascular invasion in independent datasets. Methods: The literature search yielded 318 genes related to survival and 52 related to vascular invasion. Validation was performed in three datasets (RNA-seq, n = 371; Affymetrix arrays, n = 91; Illumina gene chips, n = 135) by uni- and multivariate Cox regression and Mann–Whitney U -test, separately for Asian and Caucasian patients. Results: One hundred and eighty biomarkers remained significant in Asian and 128 in Caucasian subjects at p < 0.05. After multiple testing correction BIRC5 ( p = 1.9 × 10 ⁻¹⁰ ), CDC20 ( p = 2.5 × 10 ⁻⁹ ) and PLK1 ( p = 3 × 10 ⁻⁹ ) endured as best performing genes in Asian patients; however, none remained significant in the Caucasian cohort. In a multivariate analysis, significance was reached by stage ( p = 0.0018) and expression of CENPH ( p = 0.0038) and CDK4 ( p = 0.038). KIF18A was the only gene predicting vascular invasion in the Affymetrix and Illumina cohorts ( p = 0.003 and p = 0.025, respectively). Conclusion: Overall, about half of biomarker candidates failed to retain prognostic value and none were better than stage predicting OS. Impact: Our results help to eliminate biomarkers with limited capability to predict OS and/or vascular invasion.

Scientists from nearly all disciplines face the problem of simultaneously evaluating many hypotheses. Conducting multiple comparisons increases the likelihood that a non-negligible proportion of associations will be false positives, clouding real discoveries. Drawing valid conclusions require taking into account the number of performed statistical tests and adjusting the statistical confidence measures. Several strategies exist to overcome the problem of multiple hypothesis testing. We aim to summarize critical statistical concepts and widely used correction approaches while also draw attention to frequently misinterpreted notions of statistical inference. We provide a step-by-step description of each multiple-testing correction method with clear examples and present an easy-to-follow guide for selecting the most suitable correction technique. To facilitate multiple-testing corrections, we developed a fully automated solution not requiring programming skills or the use of a command line. Our registration free online tool is available at www.multipletesting.com and compiles the five most frequently used adjustment tools, including the Bonferroni, the Holm (step-down), the Hochberg (step-up) corrections, allows to calculate False Discovery Rates (FDR) and q-values. The current summary provides a much needed practical synthesis of basic statistical concepts regarding multiple hypothesis testing in a comprehensible language with well-illustrated examples. The web tool will fill the gap for life science researchers by providing a user-friendly substitute for command-line alternatives.

The overall prognosis for colorectal cancer (CRC) remains challenging as the survival time varies widely, even in patients with the same stage of disease. Recent studies suggest prognostic relevance of the novel markers of systemic inflammation, the systemic immune–inflammation index (SII), and the systemic inflammation response index (SIRI). We conducted a comprehensive meta-analysis to assess the prognostic significance of the SII and the SIRI in CRC. We searched the relevant literature for observational studies, and random effects models were employed to conduct a statistical analysis using the metaanalysisonline.com platform. Pooled effect sizes were reported with hazard ratios (HRs) and corresponding 95% confidence intervals (CI). Data from 29 studies published between 2016 and 2024, comprising 10,091 participants, were included in our meta-analysis on SII. CRC patients with high SII levels had worse disease outcomes, which were associated with poor OS (HR: 1.75; 95% CI: 1.4–2.19) and poor PFS/DFS/RFS (HR: 1.25; 95% CI: 1.18–1.33). This increased risk of worse OS was present irrespective of the treatment strategy, sample size (<220 and ≥220), and cutoff used to define high and low SII (<550 and ≥550) groups. Based on data from five studies comprising 2362 participants, we found a strong association between the high SIRI and worse OS (HR: 2.65; 95% CI: 1.6–4.38) and DFS/RFS (HR: 2.04; 95% CI: 1.42–2.93). According to our results, both the SII and SIRI hold great promise as prognostic markers in CRC. Further validations are needed for their age- and stage-specific utility in the clinical routine.

The hallmarks of cancer capture the most essential phenotypic characteristics of malignant transformation and progression. Although numerous factors involved in this multi-step process are still unknown to date, an ever-increasing number of mutated/altered candidate genes are being identified within large-scale cancer genomic projects. Therefore, investigators need to be aware of available and appropriate techniques capable of determining characteristic features of each hallmark. We review the methods tailored to experimental cancer researchers to evaluate cell proliferation, programmed cell death, replicative immortality, induction of angiogenesis, invasion and metastasis, genome instability, and reprogramming of energy metabolism. Selecting the ideal method is based on the investigator's goals, available equipment and also on financial constraints. Multiplexing strategies enable a more in-depth data collection from a single experiment - obtaining several results from a single procedure reduces variability and saves time and relative cost, leading to more robust conclusions compared to a single end point measurement. Each hallmark possesses characteristics that can be analyzed by immunoblot, RT-PCR, immunocytochemistry, immunoprecipitation, RNA microarray or RNA-seq. In general, flow cytometry, fluorescence microscopy, and multiwell readers are extremely versatile tools and, with proper sample preparation, allow the detection of a vast number of hallmark features. Finally, we also provide a list of hallmark-specific genes to be measured in transcriptome-level studies. Although our list is not exhaustive, we provide a snapshot of the most widely used methods, with an emphasis on methods enabling the simultaneous evaluation of multiple hallmark features.

Development of drug resistance is a major factor limiting the continued success of cancer chemotherapy. To overcome drug resistance, understanding the underlying mechanism(s) is essential. We found that HOXC10 is overexpressed in primary carcinomas of the breast, and even more significantly in distant metastasis arising after failed chemotherapy. High HOXC10 expression correlates with shorter recurrence-free and overall survival in patients with estrogen receptor–negative breast cancer undergoing chemotherapy. We found that HOXC10 promotes survival in cells treated with doxorubicin, paclitaxel, or carboplatin by suppressing apoptosis and upregulating NF-κB. Overexpressed HOXC10 increases S-phase–specific DNA damage repair by homologous recombination (HR) and checkpoint recovery in cells at three important phases. For double-strand break repair, HOXC10 recruits HR proteins at sites of DNA damage. It enhances resection and lastly, it resolves stalled replication forks, leading to initiation of DNA replication following DNA damage. We show that HOXC10 facilitates, but is not directly involved in DNA damage repair mediated by HR. HOXC10 achieves integration of these functions by binding to, and activating cyclin-dependent kinase, CDK7, which regulates transcription by phosphorylating the carboxy-terminal domain of RNA polymerase II. Consistent with these findings, inhibitors of CDK7 reverse HOXC10-mediated drug resistance in cultured cells. Blocking HOXC10 function, therefore, presents a promising new strategy to overcome chemotherapy resistance in breast cancer. Cancer Res; 76(15); 4443–56. ©2016 AACR.

SHH‐activated medulloblastomas (SHH‐MB) account for 25–30% of all medulloblastomas (MB) and occur with a bimodal age distribution, encompassing many infant and adult, but fewer childhood cases. Different age groups are characterized by distinct survival outcomes and age‐specific alterations of regulatory pathways. Here, we review SHH‐specific genetic aberrations and signaling pathways. Over 95% of SHH‐MBs contain at least one driver event – the activating mutations frequently affect sonic hedgehog signaling (PTCH1, SMO, SUFU), genome maintenance (TP53), and chromatin modulation (KMT2D, KMT2C, HAT complexes), while genes responsible for transcriptional regulation (MYCN) are recurrently amplified. SHH‐MBs have the highest prevalence of damaging germline mutations among all MBs. TP53‐mutant MBs are enriched among older children and have the worst prognosis among all SHH‐MBs. Numerous genetic aberrations, including mutations of TERT, DDX3X, and the PI3K/AKT/mTOR pathway are almost exclusive to adult patients. We elaborate on the newest development within the evolution of molecular subclassification, and compare proposed risk categories across emerging classification systems. We discuss discoveries based on preclinical models and elaborate on the applicability of potential new therapies, including BET bromodomain inhibitors, statins, inhibitors of SMO, AURK, PLK, cMET, targeting stem‐like cells, and emerging immunotherapeutic strategies. An enormous amount of data on the genetic background of SHH‐MB have accumulated, nevertheless, subgroup affiliation does not provide reliable prediction about response to therapy. Emerging subtypes within SHH‐MB offer more layered risk stratifications. Rational clinical trial designs with the incorporation of available molecular knowledge are inevitable. Improved collaboration across the scientific community will be imperative for therapeutic breakthroughs.