Bladder and upper urinary tract cancers as first and second primary cancers

Background Previous population-based studies on second primary cancers (SPCs) in urothelial cancers have focused on known risk factors in bladder cancer patients without data on other urothelial sites of the renal pelvis or ureter. Aims To estimate sex-specific risks for any SPCs after urothelial cancers, and in reverse order, for urothelial cancers as SPCs after any cancer. Such two-way analysis may help interpret the results. Methods We employed standardized incidence ratios (SIRs) to estimate bidirectional relative risks of subsequent cancer associated with urothelial cancers. Patient data were obtained from the Swedish Cancer Registry from years 1990 through 2015. Results We identified 46 234 urinary bladder cancers (75% male), 940 ureteral cancers (60% male), and 2410 renal pelvic cancers (57% male). After male bladder cancer, SIRs significantly increased for 9 SPCs, most for ureteral (SIR 41.9) and renal pelvic (17.2) cancers. In the reversed order (bladder cancer as SPC), 10 individual FPCs were associated with an increased risk; highest associations were noted after renal pelvic (21.0) and ureteral (20.9) cancers. After female bladder cancer, SIRs of four SPCs were significantly increased, most for ureteral (87.8) and pelvic (35.7) cancers. Female bladder, ureteral, and pelvic cancers associated are with endometrial cancer. Conclusions The risks of recurrent urothelial cancers were very high, and, at most sites, female risks were twice over the male risks. Risks persisted often to follow-up periods of >5 years, motivating an extended patient follow-up. Lynch syndrome-related cancers were associated with particularly female urothelial cancers, calling for clinical vigilance.Peer reviewe

A Bioinformatics Filtering Strategy for Identifying Radiation Response Biomarker Candidates

The number of biomarker candidates is often much larger than the number of clinical patient data points available, which motivates the use of a rational candidate variable filtering methodology. The goal of this paper is to apply such a bioinformatics filtering process to isolate a modest number (<10) of key interacting genes and their associated single nucleotide polymorphisms involved in radiation response, and to ultimately serve as a basis for using clinical datasets to identify new biomarkers. In step 1, we surveyed the literature on genetic and protein correlates to radiation response, in vivo or in vitro, across cellular, animal, and human studies. In step 2, we analyzed two publicly available microarray datasets and identified genes in which mRNA expression changed in response to radiation. Combining results from Step 1 and Step 2, we identified 20 genes that were common to all three sources. As a final step, a curated database of protein interactions was used to generate the most statistically reliable protein interaction network among any subset of the 20 genes resulting from Steps 1 and 2, resulting in identification of a small, tightly interacting network with 7 out of 20 input genes. We further ranked the genes in terms of likely importance, based on their location within the network using a graph-based scoring function. The resulting core interacting network provides an attractive set of genes likely to be important to radiation response

Combined analysis of HLA class I, HLA-E and HLA-G predicts prognosis in colon cancer patients

Stemcel biology/Regenerative medicine (incl. bloodtransfusion

Current state of immunotherapy for glioblastoma

Glioma is the most common primary cancer of the central nervous system, and around 50% of patients present with the most aggressive form of the disease, glioblastoma. Conventional therapies, including surgery, radiotherapy, and pharmacotherapy (typically chemotherapy with temozolomide), have not resulted in major improvements in the survival outcomes of patients with glioblastoma. Reasons for this lack of progress include invasive tumour growth in an essential organ, which limits the utility of local therapy, as well as the protection of tumour cells by the blood-brain barrier, their intrinsic resistance to the induction of cell death, and lack of dependence on single, targetable oncogenic pathways, all of which impose challenges for systemic therapy. Furthermore, the unique immune environment of the central nervous system needs to be considered when pursuing immune-based therapeutic approaches for glioblastoma. Nevertheless, a range of different immunotherapies are currently being actively investigated in patients with this disease, spurred on by advances in immuno-oncology for other tumour types. Herein, we examine the current state of immunotherapy for gliomas, notably glioblastoma, the implications for combining the current standard-of-care treatment modalities with immunotherapies, potential biomarkers of response, and future directions for glioblastoma immuno-oncology