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Cancer is a heterogeneous disease with a strong genetic component making it suitable for precision medicine approaches aimed at identifying the underlying molecular drivers within a tumour. Large scale population-level cancer sequencing consortia have identified many actionable mutations common across both cancer types and sub-types, resulting in an increasing number of successful precision medicine programs. Nonetheless, such approaches fail to consider the effects of mutations unique to an individual patient and may miss rare driver mutations, necessitating personalised approaches to driver-gene prioritisation. One approach is to quantify the functional importance of individual mutations in a single tumour based on how they affect the expression of genes in a gene interaction network (GIN). These GIN-based approaches can be broadly divided into those that utilise an existing reference GIN and those that construct de novo patient-specific GINs. These single-tumour approaches have several limitations that likely influence their results, such as use of reference cohort data, network choice, and approaches to mathematical approximation, and more research is required to evaluate the in vitro and in vivo applicability of their predictions. This review examines the current state of the art methods that identify driver genes in single tumours with a focus on GIN-based driver prioritisation.

Summary: Background: Sensitive diagnostics are needed for effective management and surveillance of schistosomiasis so that current transmission interruption goals set by WHO can be achieved. We aimed to screen the Schistosoma haematobium secretome to find antibody biomarkers of schistosome infection, validate their diagnostic performance in samples from endemic populations, and evaluate their utility as point of care immunochromatographic tests (POC-ICTs) to diagnose urogenital schistosomiasis in the field. Methods: We did a biomarker identification study, in which we constructed a proteome array containing 992 validated and predicted proteins from S haematobium and screened it with serum and urine antibodies from endemic populations in Gabon, Tanzania, and Zimbabwe. Arrayed antigens that were IgG-reactive and a select group of antigens from the worm extracellular vesicle proteome, predicted to be diagnostically informative, were then evaluated by ELISA using the same samples used to probe arrays, and samples from individuals residing in a low-endemicity setting (ie, Pemba and Unguja islands, Zanzibar, Tanzania). The two most sensitive and specific antigens were incorporated into POC-ICTs to assess their ability to diagnose S haematobium infection from serum in a field-deployable format. Findings: From array probing, in individuals who were infected, 208 antigens were the targets of significantly elevated IgG responses in serum and 45 antigens were the targets of significantly elevated IgG responses in urine. Of the five proteins that were validated by ELISA, Sh-TSP-2 (area under the curve [AUC]serum=0·98 [95% CI 0·95–1·00]; AUCurine=0·96 [0·93–0·99]), and MS3_01370 (AUCserum=0·93 [0·89–0·97]; AUCurine=0·81 [0·72–0·89]) displayed the highest overall diagnostic performance in each biofluid and exceeded that of S haematobium-soluble egg antigen in urine (AUC=0·79 [0·69–0·90]). When incorporated into separate POC-ICTs, Sh-TSP-2 showed absolute specificity and a sensitivity of 75% and MS3_01370 showed absolute specificity and a sensitivity of 89%. Interpretation: We identified numerous biomarkers of urogenital schistosomiasis that could form the basis of novel antibody diagnostics for this disease. Two of these antigens, Sh-TSP-2 and MS3_01370, could be used as sensitive, specific, and field-deployable diagnostics to support schistosomiasis control and elimination initiatives, with particular focus on post-elimination surveillance. Funding: Australian Trade and Investment Commission and Merck Global Health Institute.