Colorectal cancer exhibits a notable prevalence and propensity for metastasis, but the current therapeutic interventions for metastatic colorectal cancer have yielded suboptimal results. ICIs can decrease tumor development by preventing the tumor’s immune evasion, presenting cancer patients with a new treatment alternative. The increased use of immune checkpoint inhibitors (ICIs) in CRC has brought several issues. In particular, ICIs have demonstrated significant clinical effectiveness in patients with MSI-H CRC, whereas their efficacy is limited in MSS. Acquired resistance can still occur in patients with a positive response to ICIs. This paper describes the efficacy of ICIs currently in the clinical treatment of CRC, discusses the mechanisms by which acquired resistance occurs, primarily related to loss and impaired presentation of tumor antigens, reduced response of IFN-λ and cytokine or metabolic dysregulation, and summarizes the incidence of adverse effects. We posit that the future of ICIs hinges upon the advancement of precise prediction biomarkers and the implementation of combination therapies. This study aims to elucidate the constraints associated with ICIs in CRC and foster targeted problem-solving approaches, thereby enhancing the potential benefits for more patients.

Background: With the recent emergence of immune checkpoint inhibitors, microsatellite instability (MSI) status has become an important biomarker for immune checkpoint blockade therapy. There are growing technical demands for the integration of different genomic alterations profiling including MSI analysis in a single assay for full use of the limited tissues. Methods: Tumor and paired control samples from 64 patients with primary colorectal cancer were enrolled in this study, including 14 MSI-high (MSI-H) cases and 50 microsatellite stable (MSS) cases determined by MSI-PCR. All the samples were sequenced by a customized NGS panel covering 2.2 MB. A training dataset of 28 samples was used for selection of microsatellite loci and a novel NGS-based MSI status classifier, USCI-msi, was developed. NGS-based MSI status, single nucleotide variant (SNV) and tumor mutation burden (TMB) were detected for all patients. Most of the patients were also independently detected by immunohistochemistry (IHC) staining. Results: A 9-loci model for detecting microsatellite instability was able to correctly predict MSI status with 100% sensitivity and specificity compared with MSI-PCR, and 84.3% overall concordance with IHC staining. Mutations in cancer driver genes (APC, TP53, and KRAS) were dispersed in MSI-H and MSS cases, while BRAF p.V600E and frameshifts in TCF7L2 gene occurred only in MSI-H cases. Mismatch repair (MMR)-related genes are highly mutated in MSI-H samples. Conclusion: We established a new NGS-based MSI classifier, USCI-msi, with as few as 9 microsatellite loci for detecting MSI status in CRC cases. This approach possesses 100% sensitivity and specificity, and performed robustly in samples with low tumor purity.

// <![CDATA[ $('.header-date').hide();$('#titleAuthors').hide();$('#abstractHeader').hide(); // ]]> Haihua Ruan1, Shuangyan Hu1, Hongyu Zhang1, Gang Du1, Xiaoting Li2, Xiaobo Li2 and Xichuan Li2 1Tianjin Key Laboratory of Food Science and Biotechnology, College of Biotechnology and Food Science, Tianjin University of Commerce, Tianjin, China 2Department of Immunology, Tianjin Medical University, Tianjin, China Correspondence to: Xichuan Li, email: xichuanli@tmu.edu.cn Hongyu Zhang, email: zhanghongyu@tjcu.edu.cn Keywords: solid tumors, SOX9, prognosis, meta-analysis Received: August 23, 2017 Accepted: October 05, 2017 Published: November 06, 2017 ABSTRACT It was recently reported that increased SOX9 expression drives tumor growth and promotes cancer invasion during human tumorigenicity and metastasis. However, the prognostic value of SOX9 for the survival of patients with solid tumors remains controversial. The present meta-analysis was thus performed to highlight the link between dysregulated SOX9 expression and prognosis in cancer patients. A systematic literature search was conducted using the electronic databases PubMed, Web of Science and Embase to identify eligible studies. A random-effects meta-analytical model was employed to correlate SOX9 expression with overall survival (OS), disease-free survival (DFS) and clinicopathological features. In total, 17 studies with 3307 patients were eligible for the final analysis. Combined hazard ratios (HRs) and 95% confidence intervals (CIs) suggested that high SOX9 expression has an unfavourable impact on OS (HR = 1.66, 95% CI 1.36–2.02, P < 0.001) and DFS (HR = 3.54, 95% CI 2.29–5.47, P = 0.008) in multivariate analysis. Additionally, the pooled odds ratios (ORs) indicated that SOX9 over-expression is associated with large tumor size, lymph node metastasis, distant metastasis and a higher clinical stage. Overall, these results indicated that SOX9 over-expression in patients with solid tumors might be related to poor prognosis and could serve as a potential predictive marker of poor clinicopathological prognosis factor.

The prognostic value of p62 in solid tumor patients: a meta-analysis The prognostic value of p62 in solid tumor patients: a meta-analysis

Background: Invasive candidiasis is the most common fungal disease among hospitalized patients and continues to be a major cause of mortality. Risk factors for mortality have been studied previously but rarely developed into a predictive nomogram, especially for cancer patients. We constructed a nomogram for mortality prediction based on a retrospective review of 10 years of data for cancer patients with invasive candidiasis. Methods: Clinical data for cancer patients with invasive candidiasis during the period of 2010–2019 were studied; the cases were randomly divided into training and validation cohorts. Variables in the training cohort were subjected to a predictive nomogram based on multivariate logistic regression analysis and a stepwise algorithm. We assessed the performance of the nomogram through the area under the receiver operating characteristic (ROC) curve (AUC) and decision curve analysis (DCA) in both the training and validation cohorts. Results: A total of 207 cases of invasive candidiasis were examined, and the crude 30-day mortality was 28.0%. Candida albicans (48.3%) was the predominant species responsible for infection, followed by the Candida glabrata complex (24.2%) and Candida tropicalis (10.1%). The training and validation cohorts contained 147 and 60 cases, respectively. The predictive nomogram consisted of bloodstream infections, intensive care unit (ICU) admitted > 3 days, no prior surgery, metastasis and no source control. The AUCs of the training and validation cohorts were 0.895 (95% confidence interval [CI], 0.846–0.945) and 0.862 (95% CI, 0.770–0.955), respectively. The net benefit of the model performed better than “treatment for all” in DCA and was also better for opting low-risk patients out of treatment than “treatment for none” in opt-out DCA. Conclusion: Cancer patients with invasive candidiasis exhibit high crude mortality. The predictive nomogram established in this study can provide a probability of mortality for a given patient, which will be beneficial for therapeutic strategies and outcome improvement.