Gemcitabine-cisplatin (GP) chemotherapy is the standard first-line systemic treatment for recurrent or metastatic nasopharyngeal carcinoma (RM-NPC). In this international, double-blind, phase 3 trial ...(ClinicalTrials.gov identifier: NCT03581786), 289 patients with RM-NPC and no previous chemotherapy for recurrent or metastatic disease were randomized (1/1) to receive either toripalimab, a monoclonal antibody against human programmed death-1 (PD-1), or placebo in combination with GP every 3 weeks for up to six cycles, followed by monotherapy with toripalimab or placebo. The primary endpoint was progression-free survival (PFS) as assessed by a blinded independent review committee according to RECIST v.1.1. At the prespecified interim PFS analysis, a significant improvement in PFS was detected in the toripalimab arm compared to the placebo arm: median PFS of 11.7 versus 8.0 months, hazard ratio (HR) = 0.52 (95% confidence interval (CI): 0.36-0.74), P = 0.0003. An improvement in PFS was observed across key subgroups, including PD-L1 expression. As of 18 February 2021, a 40% reduction in risk of death was observed in the toripalimab arm compared to the placebo arm (HR = 0.603 (95% CI: 0.364-0.997)). The incidence of grade ≥3 adverse events (AEs) (89.0 versus 89.5%), AEs leading to discontinuation of toripalimab/placebo (7.5 versus 4.9%) and fatal AEs (2.7 versus 2.8%) was similar between the two arms; however, immune-related AEs (39.7 versus 18.9%) and grade ≥3 infusion reactions (7.5 versus 0.7%) were more frequent in the toripalimab arm. In conclusion, the addition of toripalimab to GP chemotherapy as a first-line treatment for patients with RM-NPC provided superior PFS compared to GP alone, and with a manageable safety profile.
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GEOZS, IJS, IMTLJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK, ZAGLJ
Cancer greatly affects the quality of life of humans worldwide and the number of patients suffering from it is continuously increasing. Over the last century, numerous treatments have been developed ...to improve the survival of cancer patients but substantial progress still needs to be made before cancer can be truly cured. In recent years, antitumor immunity has become the most debated topic in cancer research and the booming development of immunotherapy has led to a new epoch in cancer therapy. In this review, we describe the relationships between tumors and the immune system, and the rise of immunotherapy. Then, we summarize the characteristics of tumor‐associated immunity and immunotherapeutic strategies with various molecular mechanisms by showing the typical immune molecules whose antibodies are broadly used in the clinic and those that are still under investigation. We also discuss important elements from individual cells to the whole human body, including cellular mutations and modulation, metabolic reprogramming, the microbiome, and the immune contexture. In addition, we also present new observations and technical advancements of both diagnostic and therapeutic methods aimed at cancer immunotherapy. Lastly, we discuss the controversies and challenges that negatively impact patient outcomes.
In this review, we present a clear view of the major factors and regulators associated with cancer immunotherapy and to provide our point of view on the latest available technologies and treatment methods for resolving clinical problems.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The Hippo pathway plays essential roles in organ size control and cancer prevention via restricting its downstream effector, Yes‐associated protein (YAP). Previous studies have revealed an oncogenic ...function of YAP in reprogramming glucose metabolism, while the underlying mechanism remains to be fully clarified. Accumulating evidence suggests long noncoding RNAs (lncRNAs) as attractive therapeutic targets, given their roles in modulating various cancer‐related signaling pathways. In this study, we report that lncRNA breast cancer anti‐estrogen resistance 4 (BCAR4) is required for YAP‐dependent glycolysis. Mechanistically, YAP promotes the expression of BCAR4, which subsequently coordinates the Hedgehog signaling to enhance the transcription of glycolysis activators HK2 and PFKFB3. Therapeutic delivery of locked nucleic acids (LNAs) targeting BCAR4 attenuated YAP‐dependent glycolysis and tumor growth. The expression levels of BCAR4 and YAP are positively correlated in tissue samples from breast cancer patients, where high expression of both BCAR4 and YAP is associated with poor patient survival outcome. Taken together, our study not only reveals the mechanism by which YAP reprograms glucose metabolism, but also highlights the therapeutic potential of targeting YAP‐BCAR4‐glycolysis axis for breast cancer treatment.
Synopsis
Yes‐associated protein promotes cancer formation by reprogramming glucose metabolism. A long noncoding RNA BCAR4 is a key downstream effector of YAP, in regulation of glycolysis and tumorigenesis via GLI2‐mediated expression of key glycolytic enzymes.
BCAR4 is a direct transcriptional target of YAP.
BCAR4 promotes glycolysis by increasing the expression of HK2 and PFKFB3.
GLI2 activation is required for the expression of glycolytic enzymes downstream of BCAR4
High YAP and BCAR4 expression levels positively correlate in breast cancer patient samples and are linked to poor clinical outcomes.
Inhibition of BCAR4 via Locked Nucleic Acids (LNAs) attenuated YAP‐dependent glycolysis and tumor growth.
Yes‐associated protein activation triggers transcription of long noncoding RNA BCAR4, leading to GLI2‐mediated expression of key glycolytic enzymes.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Accurate risk stratification for patients with stage II/III colon cancer is pivotal for postoperative treatment decisions. Here, we aimed to identify and validate a circRNA‐based signature that could ...improve postoperative prognostic stratification for these patients. In current retrospective analysis, we included 667 patients with R0 resected stage II/III colon cancer. Using RNA‐seq analysis of 20 paired frozen tissues collected postoperation, we profiled differential circRNA expression between patients with and without recurrence, followed by quantitative validation. With clinical information, we generated a four‐circRNA‐based cirScore to classify patients into high‐risk and low‐risk groups in the training cohort. The patients with high cirScores in the training cohort had a shorter disease‐free survival (DFS) and overall survival (OS) than patients with low cirScores. The prognostic capacity of the classifier was validated in the internal and external cohorts. Loss‐of‐function assays indicated that the selected circRNAs played functional roles in colon cancer progression. Overall, our four‐circRNA‐based classifier is a reliable prognostic tool for postoperative disease recurrence in patients with stage II/III colon cancer.
Synopsis
Novel molecular biomarkers allowing for better prognostic stratification of patients with stage II/III colon cancer are urgently needed. In this study, a circRNA‐based signature (cirScore) was identified and validated to improve postoperative risk‐stratification for these patients.
Dysregulated circRNAs showed strong classification capacities in distinguishing between recurrent and nonrecurrent colon cancer patients.
The proposed four‐cirRNA‐based cirScore can effectively classify patients with stage II/III colon cancer into groups with low and high risks of disease recurrence.
The loss‐of‐function assay indicated that the representative circRNAs plays functional roles in the sophisticated regulation of colon cancer progression.
Nomograms incorporating the cirScore with existing risk factors achieved excellent accuracy for predicting disease‐free and overall survival for patients with stage II/III colon cancer.
Novel molecular biomarkers allowing for better prognostic stratification of patients with stage II/III colon cancer are urgently needed. In this study, a circRNA‐based signature (cirScore) was identified and validated to improve postoperative risk‐stratification for these patients.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Naive Bayesian classification algorithm is widely used in big data analysis and other fields because of its simple and fast algorithm structure. Aiming at the shortcomings of the naive Bayes ...classification algorithm, this paper uses feature weighting and Laplace calibration to improve it, and obtains the improved naive Bayes classification algorithm. Through numerical simulation, it is found that when the sample size is large, the accuracy of the improved naive Bayes classification algorithm is more than 99%, and it is very stable; when the sample attribute is less than 400 and the number of categories is less than 24, the accuracy of the improved naive Bayes classification algorithm is more than 95%. Through empirical research, it is found that the improved naive Bayes classification algorithm can greatly improve the correct rate of discrimination analysis from 49.5 to 92%. Through robustness analysis, the improved naive Bayes classification algorithm has higher accuracy.
Tumor cells often reprogram their metabolism for rapid proliferation. The roles of long noncoding RNAs (lncRNAs) in metabolism remodeling and the underlying mechanisms remain elusive. Through ...screening, we found that the lncRNA Actin Gamma 1 Pseudogene (AGPG) is required for increased glycolysis activity and cell proliferation in esophageal squamous cell carcinoma (ESCC). Mechanistically, AGPG binds to and stabilizes 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3). By preventing APC/C-mediated ubiquitination, AGPG protects PFKFB3 from proteasomal degradation, leading to the accumulation of PFKFB3 in cancer cells, which subsequently activates glycolytic flux and promotes cell cycle progression. AGPG is also a transcriptional target of p53; loss or mutation of TP53 triggers the marked upregulation of AGPG. Notably, inhibiting AGPG dramatically impaired tumor growth in patient-derived xenograft (PDX) models. Clinically, AGPG is highly expressed in many cancers, and high AGPG expression levels are correlated with poor prognosis, suggesting that AGPG is a potential biomarker and cancer therapeutic target.
Abstract
A more common and noninvasive predicting biomarker for programmed cell death 1 (PD-1) antibody remains to be explored. We assessed 46 patients with advanced gastric cancer who received PD-1 ...antibody immunotherapy and 425-genes next-generation sequencing (NGS) testing. Patients who had a > 25% decline in maximal somatic variant allelic frequency (maxVAF) had a longer progression free survival (PFS) and higher response rate than those who did not (7.3 months vs 3.6 months,
p
= 0.0011; 53.3% vs 13.3%,
p
= 0.06). The median PFS of patients with undetectable and detectable post-treatment circulating tumor DNA (ctDNA) was 7.4 months vs. 4.9 months (
p
= 0.025). Mutation status of TGFBR2, RHOA, and PREX2 in baseline ctDNA influenced the PFS of immunotherapy (
p
< 0.05). Patients with alterations in CEBPA, FGFR4, MET or KMT2B (
p
= 0.09) gene had greater likelihood of immune-related adverse events (irAEs). ctDNA can serve as a potential biomarker of the response to immunotherapy in advanced gastric cancers, and its potential role in predicting irAEs worth further exploration.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Although immune checkpoint inhibitor (ICI) is regarded as a breakthrough in cancer therapy, only a limited fraction of patients benefit from it. Cancer stemness can be the potential culprit in ICI ...resistance, but direct clinical evidence is lacking.
Publicly available scRNA-Seq datasets derived from ICI-treated patients were collected and analyzed to elucidate the association between cancer stemness and ICI response. A novel stemness signature (Stem.Sig) was developed and validated using large-scale pan-cancer data, including 34 scRNA-Seq datasets, The Cancer Genome Atlas (TCGA) pan-cancer cohort, and 10 ICI transcriptomic cohorts. The therapeutic value of Stem.Sig genes was further explored using 17 CRISPR datasets that screened potential immunotherapy targets.
Cancer stemness, as evaluated by CytoTRACE, was found to be significantly associated with ICI resistance in melanoma and basal cell carcinoma (both P < 0.001). Significantly negative association was found between Stem.Sig and anti-tumor immunity, while positive correlations were detected between Stem.Sig and intra-tumoral heterogenicity (ITH) / total mutational burden (TMB). Based on this signature, machine learning model predicted ICI response with an AUC of 0.71 in both validation and testing set. Remarkably, compared with previous well-established signatures, Stem.Sig achieved better predictive performance across multiple cancers. Moreover, we generated a gene list ranked by the average effect of each gene to enhance tumor immune response after genetic knockout across different CRISPR datasets. Then we matched Stem.Sig to this gene list and found Stem.Sig significantly enriched 3% top-ranked genes from the list (P = 0.03), including EMC3, BECN1, VPS35, PCBP2, VPS29, PSMF1, GCLC, KXD1, SPRR1B, PTMA, YBX1, CYP27B1, NACA, PPP1CA, TCEB2, PIGC, NR0B2, PEX13, SERF2, and ZBTB43, which were potential therapeutic targets.
We revealed a robust link between cancer stemness and immunotherapy resistance and developed a promising signature, Stem.Sig, which showed increased performance in comparison to other signatures regarding ICI response prediction. This signature could serve as a competitive tool for patient selection of immunotherapy. Meanwhile, our study potentially paves the way for overcoming immune resistance by targeting stemness-associated genes.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The ability to identify a specific cancer using minimally invasive biopsy holds great promise for improving the diagnosis, treatment selection, and prediction of prognosis in cancer. Using ...whole-genome methylation data from The Cancer Genome Atlas (TCGA) and machine learning methods, we evaluated the utility of DNA methylation for differentiating tumor tissue and normal tissue for four common cancers (breast, colon, liver, and lung). We identified cancer markers in a training cohort of 1,619 tumor samples and 173 matched adjacent normal tissue samples. We replicated our findings in a separate TCGA cohort of 791 tumor samples and 93 matched adjacent normal tissue samples, as well as an independent Chinese cohort of 394 tumor samples and 324 matched adjacent normal tissue samples. The DNA methylation analysis could predict cancer versus normal tissue with more than 95% accuracy in these three cohorts, demonstrating accuracy comparable to typical diagnostic methods. This analysis also correctly identified 29 of 30 colorectal cancer metastases to the liver and 32 of 34 colorectal cancer metastases to the lung. We also found that methylation patterns can predict prognosis and survival. We correlated differential methylation of CpG sites predictive of cancer with expression of associated genes known to be important in cancer biology, showing decreased expression with increased methylation, as expected. We verified gene expression profiles in a mouse model of hepatocellular carcinoma. Taken together, these findings demonstrate the utility of methylation biomarkers for the molecular characterization of cancer, with implications for diagnosis and prognosis.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Evidence links the liver to development of colorectal cancer (CRC). However, it remains unknown how liver function may influence CRC risk in the general population. We conducted a prospective cohort ...study in the UK Biobank of 375 693 participants who provided blood samples in 2006 to 2010. Circulating levels of liver function markers (alanine transaminase ALT, aspartate transaminase AST, total bilirubin TBIL, gamma glutamyltransferase GGT, alkaline phosphatase ALP, total protein TP and albumin ALB) were measured. Incident cancer cases were identified through linkage to the national cancer registry up to 2019. Repeated biomarker measurements were available from a subset of 11 320 participants who were re‐assessed in 2012 to 2013. After a median follow‐up of 10.0 years, we documented 2662 cases of CRC. Circulating levels of ALT, AST, TBIL, GGT, TP and ALB at baseline were inversely associated with CRC risk (P < .01), with multivariable hazard ratio (95% confidence interval) comparing decile 10 vs 1 of 0.62 (0.51‐0.75), 0.63 (0.53‐0.75), 0.85 (0.72‐1.02), 0.74 (0.61‐0.89), 0.70 (0.59‐0.84) and 0.66 (0.55‐0.79), respectively. Strengthened associations were found after recalibration for repeated measurements. The associations appeared stronger for proximal colon cancer than distal colon cancer and rectal cancer, but consistent for early‐, mid‐ and late‐onset CRC. In a large cohort of general population, the UK Biobank, higher circulating levels of ALT, AST, TBIL, GGT, TP and ALB, largely within the normal range, were associated with a lower risk of CRC. The findings support a link between liver function and CRC, and may spur future research on the gut‐microbiota‐liver axis.
What's new?
Recent studies have reported a possible relationship between circulating liver metabolites and colorectal cancer (CRC) risk, but nothing has been proven conclusively. Here, the authors examined the relationship between various circulating liver function markers and CRC risk, using data from the UK Biobank. Over 10 years of follow up, they documented 2,662 cases of CRC. They tested levels of 7 different circulating liver function markers. For 6 of the markers, higher circulating levels corresponded to a lower risk of CRC. The work may prompt future investigations into the gut‐microbiota‐liver axis.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
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