Although immune checkpoint inhibitors (ICIs) have produced remarkable responses in non-small cell lung cancer (NSCLC) patients, receivers still have a relatively low response rate. Initial response assessment by conventional imaging and evaluation criteria is often unable to identify whether patients can achieve durable clinical benefit from ICIs. Overall, there are sparse effective biomarkers identified to screen NSCLC patients responding to this therapy. A lot of studies have reported that patients with specific gene mutations may benefit from or resist to immunotherapy. However, the single gene mutation may be not effective enough to predict the benefit from immunotherapy for patients. With the advancement in sequencing technology, further studies indicate that many mutations often co-occur and suggest a drastic transformation of tumour microenvironment phenotype. Moreover, co-mutation events have been reported to synergise to activate or suppress signalling pathways of anti-tumour immune response, which also indicates a potential target for combining intervention. Thus, the different mutation profile (especially co-mutation) of patients may be an important concern for predicting or promoting the efficacy of ICIs. However, there is a lack of comprehensive knowledge of this field until now. Therefore, in this study, we reviewed and elaborated the value of cancer mutation profile in predicting the efficacy of immunotherapy and analysed the underlying mechanisms, to provide an alternative way for screening dominant groups, and thereby, optimising individualised therapy for NSCLC patients.

The prevalence of malnutrition is high among oncology patients in Northern China. Malnutrition is related to the longer hospital stay, and it can be used to predict the prognostic outcome of patients. This work focused on investigating the relationship of nutritional condition with the length of hospital stay (LOS) in Northern Chinese patients with lung adenocarcinoma (LUAD). The Patient-Generated Subjective Global Assessment (PG-SGA), Nutritional Risk Screening 2002 (NRS 2002) score, recent weight loss and BMI were assessed in a probabilistic sample of 389 LUAD patients without epidermal growth factor receptor (EGFR) mutations. This study collected the demographic and clinical features of patients in a prospective manner. Then, we examined the association of nutritional status with LOS among the population developing LUAD. According to the PG-SGA, 63 (16·3 %), 174 (44·7 %) and 78 (20·1 %) patients were at risk for undernutrition, moderate undernutrition and severe undernutrition, respectively. Nutritional risk was found in 141 (36·2 %) patients based on the NRS 2002. The average LOS for tumour patients in Northern China was 12·5 d. At admission, a risk of undernutrition or undernutrition according to the PG-SGA (P < 0·001), NRS 2002 (P < 0·001) and latest weight loss (P < 0·001) predicted the longer LOS. LOS was related to nutritional status and hospitalisation expenses (P < 0·001). LUAD patients who stayed in the ICU had a poorer nutritional status and a longer LOS (P < 0·001). In Northern Chinese patients with LUAD, a risk for undernutrition evaluated by the PG-SGA, the NRS 2002 and recent weight loss, but not BMI, could predict a longer LOS.

Many cancer-associated genes and pathways remain to be identified in order to clarify themolecular mechanisms underlying cancer progression. In this area, genome-wideloss-of-function screens appear to be powerful biological tools, allowing the accumulationof large amounts of data. However, this approach currently lacks analytical tools toexploit the data with maximum efficiency, for which systems biology methods analyzingcomplex cellular networks may be extremely helpful. In this article we report such asystems biology strategy based on the construction of a Network for a biological processand specific for a given cell system (cell type). The networks are created fromgenome-wide loss-of-function screen datasets. We also propose tools to analyze networkproperties. As one of the tools, we suggest a mathematical model for discriminationbetween two distinct cell processes that may be affected by knocking down the activity ofa gene, i. e., a decreased cell number may be caused by arrested cell proliferation orenhanced cell death. Next we show how this discrimination between the two cell processeshelps to construct two corresponding subnetworks. Finally, we demonstrate an applicationof the proposed strategy to the identification and characterization of putative novelgenes and pathways significant for the control of lung cancer cell growth, based on theresults of a genome-wide proliferation/viability loss-of-function screen of human lungadenocarcinoma cells.