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Misclassified current status data arise when the failure time of interest is observed or known only to be either smaller or larger than an observation time rather than observed exactly, and the failure status is examined by a diagnostic test with testing error. Such data commonly occur in various scientific fields, including clinical trials, demographic studies and epidemiological surveys. This paper discusses regression analysis of such data with the focus on variable selection or identifying predictable and important covariates associated with the failure time of interest. For the problem, a penalized maximum likelihood approach is proposed under the Cox proportional hazards model and the smoothly clipped absolute deviation penalty. More specifically, we develop a penalized EM algorithm to relieve the computational burden in maximizing the resulting, complex penalized likelihood function. A simulation study is conducted to examine the empirical performance of the proposed approach in finite samples, and an illustration to a set of real data on chlamydia is also provided. [ABSTRACT FROM AUTHOR]

Rationale: Thermal proteome profiling (TPP) has been widely used for the identification of drug targets for several years, and TMTpro‐16plex has recently been evaluated for TPP of vehicle‐ and drug‐treated samples in a single labeling process to reduce missing values and save instrument time. A novel isobaric labeling reagent, IBT‐16plex, was developed with slightly better performance in protein identification and quantification than the commercially available TMTpro‐16plex. Methods: In this study, we applied the newly developed IBT‐16plex for target identification of methotrexate and panobinostat using TPP. Results: The known targets of these two drugs were successfully identified with elevated melting temperatures, and some known off‐targets and potential new off‐targets were also identified. Conclusions: IBT‐16plex can be a cost‐effective replacement for TMTpro‐16plex for TPP applications. [ABSTRACT FROM AUTHOR]

Hypoxia‐inducible factor (HIF) pathway genes influence tumorigenesis and immune status. However, the associations between genetic variants in hypoxia‐related genes and colorectal cancer risk and the immune status of hypoxia‐associated genes in colorectal cancer have not been systematically characterized. The associations between genetic variants and colorectal cancer risk were evaluated in Chinese, Japanese and European populations using logistic regression analysis. The relationships between target genes and tumour immune infiltration were predicted by Tumour Immune Estimation Resource (TIMER). We found that rs34533650 in EPAS1 was associated with colorectal cancer risk (OR = 1.43, 95% CI = 1.20–1.70, P(FDR) = 8.35 × 10−4), and this finding was validated in two independent populations (Japanese: OR = 1.07, 95% CI = 1.01–1.15, p = 3.38 × 10−2; European: OR = 1.11, 95% CI = 1.03–1.19, p = 6.04 × 10−3). EPAS1‐associated genes were enriched in immune‐related pathways. In addition, we found that EPAS1 copy number variation (CNV) was associated with the degree of infiltration of immune cells and observed correlations between EPAS1 expression and immune cell infiltration levels in colorectal cancer. These results highlight that genetic variants of hypoxia‐related genes play roles in colorectal cancer risk and provide new insight that EPAS1 might be a promising predictor of colorectal cancer susceptibility and immune status. [ABSTRACT FROM AUTHOR]

Objective To investigate the role of High-mobility group box-1 (HMGB1) protein in regulating the expression of cancer stem cell markers Nanog, OCT4 and Sox2. Methods We transferred recombinant plasmid and target-specific siRNA of HMGB1 into cervical cancer cells. The expression of cancer stem cell markers (OCT4, Sox2 and Nanog) were measured by Western blot and flow cytometry. Immunohistochemical method was applied to detect HMGB1, OCT4, Sox2 and Nanog expression in 66 cases of cervical tissues. Rank correlation analysis was used to analyze their correlation. Results The full-length coding sequence of HMGB1 was 648 bp and recombined to overexpress the plasmid GV230. The selection of the highest interference rate was carried out for subsequent experiments. The protein expression and rates of stem cell markers OCT4, Sox2 and Nanog were significantly higher in HMGB1 overexpression group than those in low HMGB1 expression group and empty vector group(P < 0.05). The protein expression and rates of stem cell markers OCT4, Sox2 and Nanog were significantly lower in low HMGB1 expression group than those in HMGB1 overexpression group and empty vector group(P < 0.05). HMGB1, OCT4, Sox2 and Nanog protein expression in cervical carcinoma tissues were higher than those in chronic cervicitis tissues. Positive correlations were also found between HMGB1 and OCT4, Sox2 and Nanog expression. Conclusion HMGB1 could regulate the expression of cancer stem cell markers Nanog, OCT4 and Sox2, therefore, it is probably a potential target for anti-tumor therapy.

Summary: Interval‐censored data often arise in prospective studies involving periodical follow‐up for monitoring the failure event occurrence. In addition to censoring, left truncation also occurs if only participants who have not experienced the failure event are enrolled in the study, which clearly induces the selection bias and makes the analysis more complicated. This work provides an efficient maximum likelihood estimation approach that appropriately adjusts the biased sampling for the proportional hazards model with left‐truncated and interval‐censored data. A flexible and stable expectation–maximisation algorithm via a two‐stage data augmentation is developed to maximise the intractable likelihood function. The asymptotic properties of the proposed estimators are established with the empirical process theory. The numerical results obtained from extensive simulations suggest that the proposed method performs satisfactorily and has some prominent advantages over the competing methods. An application to a colon cancer dataset also demonstrates the usefulness of the proposed method. [ABSTRACT FROM AUTHOR]