Journal of the National Cancer Center最新文献

With increasingly explored ideologies and technologies for potential applications of artificial intelligence (AI) in oncology, we here describe a holistic and structured concept termed intelligent oncology. Intelligent oncology is defined as a cross-disciplinary specialty which integrates oncology, radiology, pathology, molecular biology, multi-omics and computer sciences, aiming to promote cancer prevention, screening, early diagnosis and precision treatment. The development of intelligent oncology has been facilitated by fast AI technology development such as natural language processing, machine/deep learning, computer vision, and robotic process automation. While the concept and applications of intelligent oncology is still in its infancy, and there are still many hurdles and challenges, we are optimistic that it will play a pivotal role for the future of basic, translational and clinical oncology.

Human papilloma virus (HPV)-associated oropharyngeal cancer (OPC) is a unique entity with increased responsiveness to treatment and excellent oncologic outcomes. The purpose of this narrative review is to highlight how an improved prognosis for HPV (+) tumors and an ever-increasing understanding of the risk factors, risk stratification, and areas of potential spread are shaping management options. Additionally, we aim to detail how advances in treatment technology on both the surgical and radiation fronts are facilitating the delivery of increasingly personalized and precise treatments. This review will describe key aspects of recent and currently-ongoing trials investigating the de-escalation and individualization of treatment in this patient cohort, and how they are building a foundation for distinct treatment paradigms for HPV (+) tumors. Further studies into the integration of biomarker-guided treatments combined with clinical trial enrollment will help ensure a future of personalized treatments and improved outcomes, both in terms of oncologic outcomes and toxicity, for patients with HPV (+) OPC.

Background

Esophageal cancer poses a significant global burden, while its patterns and trends remain to be clarified. The aim of this study is to provide an update on the incidence and mortality rates of esophageal cancer and their trends in China based on data from the National Cancer Registry.

Methods

We extracted data from the National Central Cancer Registry (NCCR) of China from 2000 to 2016 and performed comprehensive quality control. We calculated age-standardized rates of China (ASR China) and world (ASR world) using the Chinese population in 2000 and the Segi's world standard population, and performed a joinpoint regression analysis to examine the trend in incidence and mortality of esophageal cancer. The annual percent change (APC) and weighted average APC (AAPC) over the entire study period were estimated to measure the changing trend. Subgroup analyses were conducted by sex, region and pathological type.

Results

A total of 487 eligible cancer registries were included in the data analysis and 22 registries with uninterrupted registration data were used for trend analysis. In 2016, there were an estimated of 184,500 incident cases of esophageal cancer and 142,300 deaths in China. The crude incidence, ASR China and ASR world were 25.25/100,000, 11.00/100,000 and 11.13/100,000, respectively. And the crude mortality, ASR China and ASR world were 19.38/100,000, 8.25/100,000 and 8.28/100,000, respectively. Esophageal squamous cell carcinoma (ESCC) was the most common histological type, accounting for 85.79% of all cases, followed by esophageal adenocarcinoma (EAC) (11.00%) and others (3.21%). There was a decreasing trend of ASR world in incidence and mortality during 2000–2016 with the AAPC of -4.6% (95% CI: -5.7%, -3.4%) and -4.6% (95% CI: -5.2%, -3.9%). The pattern and trend of esophageal cancer differ in sex, region and pathological type.

Conclusions

The burden of esophageal cancer in China remains high with sex, regional and subtype differences. The incidence and mortality of esophageal cancer have continued to decline over the past decade, which was due in part to the reductions in risk factor exposure and the implementation of screening.

Background

The stage at diagnosis is a major factor in making treatment strategies and cancer control policies. However, the stage distribution for liver cancer in China was not well studied. In this multi-center hospital-based study, we aimed to identify the distribution and factors associated with stage at diagnosis for liver cancer in China.

Methods

We included patients diagnosed with primary liver cancer in 13 hospitals of 10 provinces covering various geographic and socioeconomic populations during 2016–2017 in China. The stage distribution overall, and by sex and age at diagnosis were analyzed. We used logistic regression to identify the factors associated with stage III-IV disease. We further compared these estimates with data from the USA.

Results

We included 2,991 patients with known stage at diagnosis in China. The proportion of patients diagnosed with stage I, II, III, and IV was 17.5%, 25.6%, 29.3%, and 27.6%, respectively. The proportion of stage III-IV cases was higher in women [65.1% vs 54.9%, adjusted odds ratio (OR) = 1.5, 95% CI: 1.2, 1.8] and those ≥ 60 years (61.6% vs 52.8%, OR = 1.4, 95% CI: 1.2, 1.6). We found an increased risk of stage III-IV among drinkers and those without a family history of cancer. Compared to the USA, our study population had a substantially higher proportion of stage III-IV cases (56.9% vs 45.6%).

Conclusion

The disparities in liver cancer stage at diagnosis among different populations within China, and between China and the USA, imply the necessity for improving cancer awareness and early detection for liver cancer in China.

Objective

To synthesize the knowledge about the association of total physical activity (TPA), leisure-time physical activity (LTPA), occupational physical activity (OPA) and lung cancer risk and explore the dose–response relationship between LTPA level and lung cancer.

Methods

PubMed and Web of Science were searched up to 17 November 2021. The summary relative risks (RRs) and 95% confidence intervals (CIs) were calculated by random-effects or fixed-effects model. The dose–response analysis was conducted with restricted cubic splines.

Results

We identified 25 articles (42 cohort studies) that assessed the physical activity–lung cancer association, including 9,983,295 study participants and 85,988 incident cases of lung cancer. When comparing the highest to the lowest level of TPA and LTPA, lung cancer risk reduced 22% (RR, 0.78; 95% CI: 0.70, 0.86) and 12% (RR, 0.88; 95% CI: 0.83, 0.93), respectively. We found an approximately U-shaped association between LTPA and lung cancer (P _{non-linearity} < 0.001), with the lowest risk at 15 metabolic equivalent of task hours per week (h/wk) of LTPA. Compared to participants with sitting occupations, lung cancer risk significantly increased among those being unemployed (RR, 1.33; 95% CI: 1.17, 1.51) or with standing occupations (RR, 1.37; 95% CI: 1.15, 1.63), but not among those with light or high OPA.

Conclusions

Our meta-analysis supported a protective effect of TPA and LTPA, but not OPA, on lung cancer risk. The novel finding of a U-shaped association between LTPA and lung cancer risk warrants further investigation.

Background

The incidence of early-onset colorectal cancer (EOCRC) has increased globally since the early 1990s. Comprehensively examining the risk factors would be helpful for risk stratification and the development of personalized colorectal cancer screening strategies.

Methods

We performed a prospective study of the Chinese population aged 30–50 years to identify potential risk factors during a median follow-up of 9.1 years. We compared the distribution of demographic characteristics, lifestyle factors, dietary habits, and medical history among 222 EOCRC cases and 87,833 normal controls. Multivariate adjusted Cox hazard models were used for estimating EOCRC risks of each risk factor.

Results

Our final analyses indicated that participants with a higher body mass index (HR, 1.04; 95% CI:1.00,1.08), regular alcohol consumption (HR, 1.69; 95% CI: 1.12, 2.91), higher intake of fish (HR, 1.64; 95% CI: 1.01, 2.67), hypertension (HR, 1.99; 95% CI: 1.04, 3.81), diabetes (HR, 2.20; 95% CI: 1.08, 4.49), and first-degree relatives with cancer (HR, 1.70; 95% CI: 1.23, 2.36) were at higher risk of EOCRC.

Conclusion

We identified several modifiable as well as nonmodifiable risk factors, such as higher BMI, alcohol and fish consumption, hypertension, and diabetes, were associated with EOCRC.

Background

Tumour mutational burden (TMB) has emerged as a predictive marker for responsiveness to immune checkpoint inhibitors (ICI) in multiple tumour types. It can be calculated from somatic mutations detected from whole exome or targeted panel sequencing data. As mutations are unevenly distributed across the cancer genome, the clinical implications from TMB calculated using different genomic regions are not clear.

Methods

Pan-cancer data of 10,179 samples were collected from The Cancer Genome Atlas cohort and 6,831 cancer patients with either ICI or non-ICI treatment outcomes were derived from published papers. TMB was calculated as the count of non-synonymous mutations and normalised by the size of genomic regions. Dirichlet method, linear regression and Poisson calibration models are used to unify TMB from different gene panels.

Results

We found that panels based on cancer genes usually overestimate TMB compared to whole exome, potentially leading to misclassification of patients to receive ICI. The overestimation is caused by positive selection for mutations in cancer genes and cannot be completely addressed by the removal of mutational hotspots. We compared different approaches to address this discrepancy and developed a generalised statistical model capable of interconverting TMB derived from whole exome and different panel sequencing data, enabling TMB correction for patient stratification for ICI treatment. We show that in a cohort of lung cancer patients treated with ICI, when using a TMB cutoff of 10 mut/Mb, our corrected TMB outperforms the original panel-based TMB.

Conclusion

Cancer gene-based panels usually overestimate TMB, and these findings will be valuable for unifying TMB calculations across cancer gene panels in clinical practice.