Sampling strategies to evaluate the prognostic value of a new biomarker on a time-to-event end-point

The Current Progress and Future Options of Multiple Therapy and Potential Biomarkers for Muscle-Invasive Bladder Cancer

Bladder cancer is a common disease in men and the elderly. Current treatment paradigms include radical resection of the bladder and lymph nodes or transurethral resection, both supported by chemotherapy and/or radiation. New modalities, such as illumination-based therapies are also being translationally pursued. However, while survival rates have increased due to combined therapies (particularly chemotherapy, radiation, immune checkpoint inhibitors, and surgery), a lack of diagnostic markers leads clinical professionals to rely on frequently invasive and expensive means of monitoring, such as magnetic resonance imaging or bladder cystoscopy. To improve real-time diagnostic capabilities, biomarkers that reflect both the metabolic and metastatic potential of tumor cells are needed. Furthermore, indicators of therapy resistance would allow for rapid changes in treatment to optimize survival outcomes. Fortunately, the presence of nanoscale extracellular vesicles in the blood, urine, and other peripheral fluids allow for proteomic, genomic, and transcriptomic analyses while limiting the invasiveness of frequent sampling. This review provides an overview of the pathogenesis and progression of bladder cancer, standard treatments and outcomes, some novel treatment studies, and the current status of biomarker and therapy development featuring exosome-based analysis and engineering.

New weighting methods when cases are only a subset of events in a nested case-control study

Nested case control (NCC) is a sampling method widely used for developing and evaluating risk models with expensive biomarkers on large prospective cohort studies. In a typical NCC design, biomarker values are obtained on a subcohort, where cases consist of all the events (subjects who experience the event during the follow-up). However, when the number of events is not small, due to the cost and limited availability of biospecimen, one may select only a subset of events as cases. We refer to such a variation as the untypical NCC. Unfortunately, existing inverse probability weighted (IPW) estimators for the untypical NCC are biased, and they only focus on relative risk parameters under the proportional hazards (PH) model. In this manuscript, we propose new weighting methods that produce consistent IPW estimators for not only relative risk parameters but also several metrics that evaluate a risk model's predictive performance. We also provide the inference procedure via perturbation resampling, which captures all the variance and between-subject covariance induced by the sampling processes for both case and control selections. In addition, our methods are not limited to the PH model, and they can be applied to the time-specific generalized linear model. Under the typical NCC design, our new weights are equivalent to the weight proposed by Samuelsen; under the untypical NCC, the IPW estimators using our weights have smaller bias and variance than the existing methods. We will demonstrate this improved performance via both analytical and numerical investigations.

SAMHD1 as a prognostic and predictive biomarker in stage II colorectal cancer: A multicenter cohort study

Background

The identification of high-risk population patients is key to the personalized treatment options for the stage II colorectal cancers. The use of proteomics in the prognosis of patients with stage II colorectal cancer remains unclear.

Methods

Using quantitative proteomics, we analyzed proteins that are differentially expressed in the tumor and adjacent normal tissues of 11 paired colorectal cancer patients with and without recurrence selected by a nested case-control design. Of the 21 identified proteins, we selected one candidate protein. The association of the corresponding gene of the selected protein with overall survival (OS) and adjuvant chemotherapy was analyzed using two independent cohorts of patients with stages II colorectal cancer.

Results

Sterile α motif and histidine-aspartate domain-containing protein 1 (SAMHD1) was selected as the candidate biomarker. A group of 124 patients (12.5%) were stratified into SAMHD1-high subgroup. The 5-year OS rate of SAMHD1-high patients was lower than that of SAMHD1-low patients with stage II colorectal cancer (discovery cohort: hazard ratio [HR] = 2.89, 95% confidence interval [CI], 1.17-7.18, P = 0.016; validation cohort: HR = 2.25, 95% CI, 1.17-4.34, P = 0.013). The Cox multivariate analysis yielded similar results. In a pooled database, the 5-year OS rate was significantly different between patients with and without adjuvant chemotherapy among stage II SAMHD1-low tumors than in patients with stage II SAMHD1-high tumors (88% vs. 77%, P = 0.032).

Conclusions

SAMHD1-high expression could help in identifying patients with stage II colorectal cancer with poor prognosis and less benefit from adjuvant chemotherapy.