Cancer survival statistics for patients and healthcare professionals - a tutorial of real-world data analysis

Unraveling cancer progression pathways and phytochemical therapeutic strategies for its management

Cancer prevention is currently envisioned as a molecular-based approach to prevent carcinogenesis in pre-cancerous stages, i.e., dysplasia and carcinoma in situ. Cancer is the second-leading cause of mortality worldwide, and a more than 61% increase is expected by 2040. A detailed exploration of cancer progression pathways, including the NF-kβ signaling pathway, Wnt-B catenin signaling pathway, JAK-STAT pathway, TNF-α-mediated pathway, MAPK/mTOR pathway, and apoptotic and angiogenic pathways and effector molecules involved in cancer development, has been discussed in the manuscript. Critical evaluation of these effector molecules through molecular approaches using phytomolecules can intersect cancer formation and its metastasis. Manipulation of effector molecules like NF-kβ, SOCS, β-catenin, BAX, BAK, VEGF, STAT, Bcl2, p53, caspases, and CDKs has played an important role in inhibiting tumor growth and its spread. Plant-derived secondary metabolites obtained from natural sources have been extensively studied for their cancer-preventing potential in the last few decades. Eugenol, anethole, capsaicin, sanguinarine, EGCG, 6-gingerol, and resveratrol are some examples of such interesting lead molecules and are mentioned in the manuscript. This work is an attempt to put forward a comprehensive approach to understanding cancer progression pathways and their management using effector herbal molecules. The role of different plant metabolites and their chronic toxicity profiling in modulating cancer development pathways has also been highlighted.

Dihydroartemisinin-driven selective anti-lung cancer proliferation by binding to EGFR and inhibition of NRAS signaling pathway-induced DNA damage

Chemotherapeutic agents can inhibit the proliferation of malignant cells due to their cytotoxicity, which is limited by collateral damage. Dihydroartemisinin (DHA), has a selective anti-cancer effect, whose target and mechanism remain uncovered. The present work aims to examine the selective inhibitory effect of DHA as well as the mechanisms involved. The findings revealed that the Lewis cell line (LLC) and A549 cell line (A549) had an extremely rapid proliferation rate compared with the 16HBE cell line (16HBE). LLC and A549 showed an increased expression of NRAS compared with 16HBE. Interestingly, DHA was found to inhibit the proliferation and facilitate the apoptosis of LLC and A549 with significant anti-cancer efficacy and down-regulation of NRAS. Results from molecular docking and cellular thermal shift assay revealed that DHA could bind to epidermal growth factor receptor (EGFR) molecules, attenuating the EGF binding and thus driving the suppressive effect. LLC and A549 also exhibited obvious DNA damage in response to DHA. Further results demonstrated that over-expression of NRAS abated DHA-induced blockage of NRAS. Moreover, not only the DNA damage was impaired, but the proliferation of lung cancer cells was also revitalized while NRAS was over-expression. Taken together, DHA could induce selective anti-lung cancer efficacy through binding to EGFR and thereby abolishing the NRAS signaling pathway, thus leading to DNA damage, which provides a novel theoretical basis for phytomedicine molecular therapy of malignant tumors.

Income disparities in loss in life expectancy after colon and rectal cancers: a Swedish register-based study

BACKGROUND

Differences in the prognosis after colorectal cancer (CRC) by socioeconomic position (SEP) have been reported previously; however, most studies focused on survival differences at a particular time since diagnosis. We quantified the lifetime impact of CRC and its variation by SEP, using individualised income to conceptualise SEP.

METHODS

Data included all adults with a first-time diagnosis of colon or rectal cancers in Sweden between 2008 and 2021. The analysis was done separately for colon and rectal cancers using flexible parametric models. For each cancer and income group, we estimated the life expectancy in the absence of cancer, the life expectancy in the presence of cancer and the loss in life expectancy (LLE).

RESULTS

We found large income disparities in life expectancy after a cancer diagnosis, with larger differences among the youngest patients. Higher income resulted in more years lost following a cancer diagnosis. For example, 40-year-old females with colon cancer lost 17.64 years if in the highest-income group and 13.68 years if in the lowest-income group. Rectal cancer resulted in higher LLE compared with colon cancer. Males lost a larger proportion of their lives. All patients, including the oldest, lost more than 30% of their remaining life expectancy. Based on the number of colon and rectal cancer diagnoses in 2021, colon cancer results in almost double the number of years lost compared with rectal cancer (24 669 and 12 105 years, respectively).

CONCLUSION

While our results should be interpreted in line with what individualised income represents, they highlight the need to address inequalities.

Avoiding lead-time bias by estimating stage-specific proportions of cancer and non-cancer deaths

PURPOSE

Understanding how stage at cancer diagnosis influences cause of death, an endpoint that is not susceptible to lead-time bias, can inform population-level outcomes of cancer screening.

METHODS

Using data from 17 US Surveillance, Epidemiology, and End Results registries for 1,154,515 persons aged 50-84 years at cancer diagnosis in 2006-2010, we evaluated proportional causes of death by cancer type and uniformly classified stage, following or extrapolating all patients until death through 2020.

RESULTS

Most cancer patients diagnosed at stages I-II did not go on to die from their index cancer, whereas most patients diagnosed at stage IV did. For patients diagnosed with any cancer at stages I-II, an estimated 26% of deaths were due to the index cancer, 63% due to non-cancer causes, and 12% due to a subsequent primary (non-index) cancer. In contrast, for patients diagnosed with any stage IV cancer, 85% of deaths were attributed to the index cancer, with 13% non-cancer and 2% non-index-cancer deaths. Index cancer mortality from stages I-II cancer was proportionally lowest for thyroid, melanoma, uterus, prostate, and breast, and highest for pancreas, liver, esophagus, lung, and stomach.

CONCLUSION

Across all cancer types, the percentage of patients who went on to die from their cancer was over three times greater when the cancer was diagnosed at stage IV than stages I-II. As mortality patterns are not influenced by lead-time bias, these data suggest that earlier detection is likely to improve outcomes across cancer types, including those currently unscreened.

Loss in life expectancy in patients with stage II-III cutaneous melanoma in Sweden: A population-based cohort study

BACKGROUND

Survival in cutaneous melanoma (CM) is heterogeneous. Loss in life expectancy (LLE) measures impact of CM on remaining lifespan compared to general population.

OBJECTIVES

Investigating LLE in operated stage II-III CM patients.

METHODS

Data from 8061 patients (aged 40-80 years) with stage II-III CM in Sweden, diagnosed between 2005 and 2018, were analyzed (Swedish Melanoma Registry). A flexible parametric survival model estimated life expectancy and LLE.

RESULTS

Based on 2018 diagnoses, stage II and III CM patients lost 2209 and 1902 life years, respectively. LLE was higher in stage III: 5.2 versus 10.9 years (stage II vs III 60-year-old females). Younger patients had higher LLE: 10.7 versus 3.9 years (stage II CM in 40 vs 70-year-old males). In stage II, females had lower LLE than males; 50-year-old females and males stage II CM had LLE equal to 7.3 and 8.3 years, respectively. LLE increased with higher substages, stage IIB resembling IIIB and IIC resembling IIIC-D.

LIMITATIONS

Extrapolation was used to estimate LLE. Varying stage group sizes require caution.

CONCLUSIONS

Our results are both clinically relevant and easy-to-interpret measures of the impact of CM on survival, but the results also summarize the prognosis over the lifetime of a CM patient.

LASSO-derived prognostic model predicts cancer-specific survival in advanced pancreatic ductal adenocarcinoma over 50 years of age: a retrospective study of SEER database research

Background

This study aimed to develop a prognostic model for patients with advanced ductal adenocarcinoma aged ≥50 years.

Methods

Patient information was extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Least absolute shrinkage and selection operator (LASSO) Cox regression analysis was performed to screen the model variables. Cases from Nanchang Central Hospital were collected for external validation. The new nomogram and the American Joint Committee on Cancer (AJCC) criteria were evaluated using integrated discrimination improvement (IDI) and net reclassification index (NRI) indicators. Survival curves presented the prognosis of the new classification system and AJCC criteria.

Results

In total, 17,621 eligible patients were included. Lasso Cox regression selected 4 variables including age, chemotherapy, radiotherapy and AJCC stage. The C-index of the training cohort was 0.721. The C-index value of the validation cohort was 0.729. The AUCs for the training cohorts at 1, 2, and 3 years were 0.749, 0.729, and 0.715, respectively. The calibration curves showed that the predicted and actual probabilities at 1, 2, and 3 years matched. External validation confirmed the model's outstanding predictive power. Decision curve analysis indicated that the clinical benefit of the nomogram was higher than that of the AJCC staging system. The model evaluation indices preceded the AJCC staging with NRI (1-year: 0.88, 2-year: 0.94, 3-year: 0.72) and IDI (1-year: 0.24, 2-year: 0.23, 3-year: 0.22). The Kaplan-Meier curves implied that the new classification system was more capable of distinguishing between patients at different risks.

Conclusions

This study established a prognostic nomogram and risk classification system for advanced pancreatic cancer in patients aged ≥50 years to provide a practical tool for the clinical management of patients with pancreatic ductal adenocarcinoma.

m6A-mediated lncRNA NEAT1 plays an oncogenic role in non-small cell lung cancer by upregulating the HMGA1 expression through binding miR-361-3p

BACKGROUND

Lung cancer is the most common primary malignant tumor of the lung, and 85% of lung cancer is non-small cell lung cancer (NSCLC). The N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) have been widely reported to participate in the development of non-small cell lung cancer.

OBJECTIVE

However, the potential molecular mechanisms of m6A-regulated lncRNAs in NSCLC still need further investigation.

METHODS

The expression levels and the role of lncRNA NEAT1 in NSCLC tissues or cells were measured by RT-qPCR, Western blot, cell counting kit 8 (CCK-8), flow cytometry assay. RNA immunoprecipitation (RIP) was used to measure the levels of m6A modification of NEAT1. Bioinformatics analysis and dual-luciferase reporter gene assay were detected the relationship between miR-361-3p and NEAT1/HMGA1. Mouse xenograft tumor models were established to confirm the effects of lncRNA NEAT1 in vivo.

RESULTS

In this study, we verified whether m6A-modified lncRNA nuclear enriched abundant transcript 1 (NEAT1) is involved in NSCLC progression via miR-361-3p/HMGA1 axis. Firstly, we found that lncRNA NEAT1 was upregulated in NSCLC, and was associated with a poor survival in NSCLC patients. Methyltransferase like 3 (METTL3)-mediated m6A modification stabilized and upregulated NEAT1 expression. Next, function experiment indicated that depletion of METTL3 and NEAT1 induced cell apoptosis and inhibited cell proliferation, epithelial-mesenchymal transition (EMT). Likewise, in vivo experiments further supported the oncogenic role of NEAT1 in NSCLC. In addition, the molecular mechanism was uncovered in our study, and we found that lncRNA NEAT1 promoted the expression of high-mobility group AT-hook 1 (HMGA1) by sponging miR-361-3p and then promoted tumorigenesis of NSCLC.

CONCLUSION

In conclusion, our findings demonstrated that METTL3-mediated m6A modification accelerated NSCLC progression by regulating the NEAT1/miR-361-3p/HMGA1 axis, which provides important targets for the treatment of NSCLC.

Real-World Data: Applications and Relevance to Cancer Clinical Trials

Randomized controlled trials (RCTs) are the gold standard for comparative-effectiveness research (CER). Since the 1980s, there has been a rise in the creation and utilization of large national cancer databases to provide readily accessible "real-world data" (RWD). This review article discusses the role of RCTs in oncology, and the role of RWD from the national cancer database in CER. RCTs remain the preferred study type for CER because they minimize confounding and bias. RCTs have challenges to conduct, including extensive time and resources, but these factors do not impact the internal validity of the result. Generalizability and external validity are potential limitations of RCTs. RWD is ideal for studying cancer epidemiology, patterns of care, disparities in care delivery, quality-of-care evaluation, and applicability of RCT data in specific populations excluded from RCTs. However, retrospective databases with RWD have limitations in CER due to unmeasured confounders and are often suboptimal in identifying causal treatment effects.

The optimal dose of Ramelteon for the better treatment adherence of delayed sleep-wake phase disorder: a dropout rate study

Background

Evidence regarding the effectiveness of melatonin receptor agonists in treating delayed sleep-wake phase disorder (DSWPD) remains limited. This study aimed to determine the optimal dose of ramelteon, a melatonin receptor agonist, for the better treatment adherence of DSWPD.

Methods

The patients who were diagnosed definitely as having DSWPD by board-certified physicians specialized in sleep medicine and started to receive strategically timed ramelteon medications after the diagnosis were included. Data on the initial ramelteon dose and follow-up duration (up to 24 months) were collected retrospectively. Patients with treatment discontinuation, changes in ramelteon dose, or the addition of other sleep-related medications were considered dropouts. Kaplan-Meier estimates, log-rank tests, and Cox regression analyses were performed.

Results

Overall, 373 patients were analyzed. The findings revealed that the 2 mg dose of ramelteon was associated with a lower dropout rate compared to the other doses (8 mg, 4 mg, and 1 mg). The dropout rate for the 2 mg group was estimated to have a hazard ratio (HR) of 0.5762 when compared with the 8 mg dose group. Sex did not reveal a significant HR, whereas older age exhibited a small but significant HR (0.9858).

Conclusion

For achieving better adherence, a dosing regimen of strategically timed 2 mg ramelteon may be the best for the treatment of DSWPD. The therapeutic dose window for better adherence seems to center approximately 2 mg of ramelteon. Furthermore, caution should be exercised when treating younger patients to prevent dropouts.

Survival of 48866 cancer patients: results from Nantong area, China

Objective

This study aimed to provide a realistic observation of survival by major site for 48,866 cancer patients treated at a tertiary cancer hospital in a rural area of China.

Methods

Patients with cancer registered between 2007 and 2017 in the Nantong rural area were followed up. The starting date for survival calculation was the date of the first diagnosis of cancer at the Nantong Tumor Hospital, and the closing date was December 31, 2020. Observed survival (OS) was analyzed according to ICD-10 site, sex, age, region, and hospitalization period using the life table method and compared using the Wilcoxon (Gehan) statistic.

Results

The overall 5-year OS rate was 40.48% for all 48,866 patients, 30.19% for males, and 51.90% for females. The top five cancer sites, accounting for 60.51% of the total cases, were the esophagus, lung, stomach, liver, and cervix, with 5-year OS rates of 33.72%, 18.64%, 32.10%, 19.04%, and 71.51%, respectively. The highest 5-year OS was observed in the thyroid (87.52%) and the lowest was in the pancreas (6.37%). Survival was significantly higher in younger patients than in older patients, with 5-year OSs of 69.26% and 19.84% in those aged 20-29 and 90-99 years, respectively. Five-year OSs improved significantly from 39.35% in 2007-2011 to 41.26% in 2012-2017.

Conclusion

Overall survival improved over the years, although the improvement at some sites was not significant. The observed survival varies from region to region, reflecting differences in the patterns of major sites, disparities in proportions of hospitalization, and demographic characteristics.

Methods for Inclusive Underwriting of Breast Cancer Risk with Machine Learning and Innovative Algorithms

INTRODUCTION

-Due to early detection and improved therapies, the prevalence of long-term breast cancer survivors is increasing. This has increased the need for more inclusive underwriting in individuals with a history of breast cancer. Herein, we developed a method using algorithm aiming facilitating the underwriting of multiple parameters in breast cancer survivors.

METHODS

-Variables and data were extracted from the SEER database and analyzed using 4 different machine learning based algorithms (Logistic Regression, GA2M, Random Forest, and XGBoost) that were compared with Kaplan Meier survival estimates. The performances of these algorithms have been compared with multiple metrics (Log Loss, AUC, and SMR). In situ (non-invasive) and metastatic breast cancer were excluded from this analysis.

RESULTS

-Parameters included the pathological subtype, pTNM staging (T: tumor size, N; number of nodes; M presence or absence of metastases), Scarff-Bloom-Richardson grading, the expression of estrogen and progesterone hormone receptors were selected to predict the individual outcome at any time point from diagnosis. While all models had identical performance in terms of statistical metrics (AUC, Log Loss, and SMR), the logistic regression was the one and only model that respects all business constraints and was intelligible for medical and underwriting users.

CONCLUSION

-This study provides insight to develop algorithms to set underwriter-friendly calculators for more accurate risk estimations that can be used to rationalize insurance pricing for breast cancer survivors. This study supports the development of a more inclusive underwriting based on models that can encompass the heterogeneity of several malignancies such as breast cancer.

Latent class analysis-derived classification improves the cancer-specific death stratification of molecular subtyping in colorectal cancer

The molecular subtypes of colorectal cancer (CRC) represent a comprehensive dissection of CRC heterogeneity. However, molecular feature-based classification systems have limitations in accurately prognosticating stratification due to the inability to distinguish cancer-specific deaths. This study aims to establish a classification system that bridges clinical characteristics, cause-specific deaths, and molecular features. We adopted latent class analysis (LCA) on 491,107 first primary CRC patients from the Surveillance, Epidemiology, and End Results (SEER) database to reveal hidden profiles of CRC. The LCA-derived classification scheme was further applied to The Cancer Genome Atlas (TCGA) to assess its effectiveness in improving the accurate stratification of molecular-based subtypes of CRC. Four classes were identified based on latent class analysis integrating demographic and clinicopathological information of CRC patients. The LCA-derived Class 1 (LCAC1) and the LCAC2 showed a high risk of dying from non-CRC, while patients in LCAC3 had a risk of dying from CRC 1.41 times that of LCAC1 (95% confidence interval [CI] = 1.39-1.43). LCAC4 had the lowest probability to die from non-CRC (hazard ratio [HR] = 0.22, 95% CI = 0.21-0.24) compared with LCAC1. Since the LCA-derived classification can identify patients susceptible to CRC-specific death, adjusting for this classification allows molecular-based subtypes to achieve more accurate survival stratification. We provided a classification system capable of distinguish CRC-specific death, which will improve the accuracy of consensus molecular subtypes for CRC patients' survival stratification. Further studies are warranted to confirm the molecular features of LCA-derived classification to inform potential therapeutic strategies and treatment recommendations.

Number of life-years lost at the time of diagnosis and several years post-diagnosis in patients with solid malignancies: a population-based study in the Netherlands, 1989-2019

Background

Loss of life expectancy (LOLE) may provide more intuitive information on the impact of cancer than relative survival over a fixed time horizon (e.g., 5-year relative survival). We aimed to assess the evolution of the LOLE using a nationwide, population-based cohort including patients diagnosed with one of 17 most frequent solid malignancies.

Methods

From the Netherlands Cancer Registry, we selected adult patients diagnosed with one of the 17 most frequent solid malignancies in the Netherlands during 1989-2019, with survival follow-up until 2022. We used flexible parametric survival models to estimate the LOLE at diagnosis and the LOLE after surviving several years post-diagnosis (conditional LOLE; CLOLE) by cancer type, calendar year, age, sex, and disease stage.

Findings

For all cancers combined, the LOLE consistently decreased from 1989 to 2019. This decrease was most pronounced for males with prostate cancer (e.g., from 6.9 [95% confidence interval [CI], 6.7-7.1] to 2.7 [95% CI, 2.5-3.0] for 65-year-olds) and females with breast cancer (e.g., from 6.6 [95% CI, 6.4-6.7] to 1.9 [95% CI, 1.8-2.0] for 65-year-olds). The LOLE among patients with cancers of the head and neck or the central nervous system remained constant over time. Overall, the CLOLE showed that the life years lost among patients with cancer decreased with each additional year survived post-diagnosis. For example, the LOLE at diagnosis for 65-year-old females diagnosed with breast cancer in 2019 was 1.9 [95% CI, 1.8-2.0] compared with 1.7 [95% CI, 1.6-1.8], 1.0 [95% CI, 0.9-1.1], and 0.5 [95% CI, 0.5-0.6] when surviving one, five, and ten years post-diagnosis, respectively. Estimates for other combinations of patient and tumour characteristics are available in a publicly available web-based application.

Interpretation

Our findings suggested that the evolution of LOLE substantially varies across cancer type, age, and disease stage. LOLE estimates help patients better understand the impact of their specific cancer diagnosis on their life expectancy.

Funding

None.

What is relative survival and what is its role in haematology?

In many haematological diseases, the survival probability is the key outcome. However, when the population of patients is rather old and the follow-up long, a significant proportion of deaths cannot be attributed to the studied disease. This lessens the importance of common survival analysis measures like overall survival and shows the need for other outcome measures requiring more complex methodology. When disease-specific information is of interest but the cause of death is not available in the data, relative survival methodology becomes crucial. The idea of relative survival is to merge the observed data set with the mortality data in the general population and thus allow for an indirect estimation of the burden of the disease. In this work, an overview of different measures that can be of interest in the field of haematology is given. We introduce the crude mortality that reports the probability of dying due to the disease of interest; the net survival that focuses on excess hazard alone and presents the key measure in comparing the disease burden of patients from populations with different general population mortality; and the relative survival ratio which gives a simple comparison of the patients' and the general population survival. We explain the properties of each measure, and some brief notes are given on estimation. Furthermore, we describe how association with covariates can be studied. All the methods and their estimators are illustrated on a sub-cohort of older patients who received a first allogeneic hematopoietic stem cell transplantation for myelodysplastic syndromes or secondary acute myeloid leukemia, to show how different methods can provide different insights into the data.

Prognosis and conditional nomogram of cervical spine fracture in patients with severe spinal cord injury: a multicenter retrospective study

INTRODUCTION

Cervical spine fractures with severe spinal cord injury (SCI) are common following cervical spine trauma and are associated with a high mortality rate. Understanding the mortality patterns of patients with cervical spine fractures and severe SCI can offer valuable evidence to surgeons and family members who are required to make critical healthcare decisions. The authors aimed to evaluate the instantaneous death risk and conditional survival (CS) of such patients and developed conditional nomograms to account for different periods of survivors and predict the survival rates.

METHODS

Their instantaneous death risks were calculated using the hazard function, and the Kaplan-Meier method was used to evaluate the survival rates. Cox regression was used to choose the variables for the construction of the nomograms. The area under the receiver operating characteristic curve and calibration plots were used to validate the performance of the nomograms.

RESULTS

The authors finally included 450 patients with cervical spine fractures and severe SCI using propensity score matching. The instantaneous death risk was the highest during the first 12 months after injury. Surgical treatment can help decrease the instantaneous death risk quickly, especially in early-term surgery. The 5-year CS increased constantly from 73.3% at baseline to 88.0% after 2 years of survival. Conditional nomograms were constructed at baseline and in those who survived for 6 and 12 months. The area under the receiver operating characteristic curve and calibration curves indicated that the nomograms had a good performance.

CONCLUSION

Their results improve our understanding of the instantaneous death risk of patients in different periods following injury. CS demonstrated the exact survival rate among medium-term and long-term survivors. Conditional nomograms are suitable for different survival periods in predicting the probability of survival. Conditional nomograms help in understanding the prognosis and improve the shared decision-making approaches.

The interactions of docetaxel with tumor microenvironment

There are several interactions within the tumor microenvironment (TME) that affect the response of cancer cells to therapy. There are also a large number of cells and secretions in TME that increase resistance to therapy. Following the release of immunosuppressive, pro-angiogenic, and metastatic molecules by certain cells such as tumor-associated macrophages (TAMs), cancer-associated fibroblasts (CAFs), and cancer cells, immune evasion, angiogenesis, and metastasis may be induced. However, natural killer (NK) cells and cytotoxic CD8 + T lymphocytes (CTLs) can responsively release anticancer molecules. In addition, anticancer drugs can modulate these cells and their interactions in favor of either cancer resistance or therapy. Docetaxel belongs to taxanes, a class of anti-tumor drugs, which acts through the polymerization of tubulin and the induction of cell cycle arrest. Also, it has been revealed that taxanes including docetaxel affect cancer cells and the other cells within TME through some other mechanisms such as modulation of immune system responses, angiogenesis, and metastasis. In this paper, we explain the basic mechanisms of docetaxel interactions with malignant cells. Besides, we review the diverse effects of docetaxel on TME and cancer cells in consequence. Lastly, the modulatory effects of docetaxel alone or in conjunction with other anticancer agents on anti-tumor immunity, cancer cell resistance, angiogenesis, and metastasis will be discussed.

Prevalence of comorbidities and their impact on survival among older adults with the five most common cancers in Taiwan: a population study

Because of the cancer incidence increase and population aging in Taiwan, we aimed to assess the cancer prevalence, to summarize the comorbidities of older patients with the five most common cancers (i.e., breast, colorectal, liver, lung, and oral), and to develop a Taiwan cancer comorbidity index (TCCI) for studying their actual prognosis. The linkage of the Taiwan Cancer Registry, Cause of Death Database, and National Health Insurance Research Database was used. We followed the standard statistical learning steps to obtain a survival model with good discriminatory accuracy in predicting death due to noncancer causes, from which we obtained the TCCI and defined comorbidity levels. We reported the actual prognosis by age, stage, and comorbidity level. In Taiwan, cancer prevalence nearly doubled in 2004-2014, and comorbidities were common among older patients. Stage was the major predictor of patients' actual prognoses. For localized and regional breast, colorectal, and oral cancers, comorbidities correlated with noncancer-related deaths. Compared with the US, the chances of dying from comorbidities in Taiwan were lower and the chances of dying from cancer were higher for breast, colorectal, and male lung cancers. These actual prognoses could help clinicians and patients in treatment decision-making and help policymakers in resource planning.

Machine learning in metastatic cancer research: Potentials, possibilities, and prospects

Cancer has received extensive recognition for its high mortality rate, with metastatic cancer being the top cause of cancer-related deaths. Metastatic cancer involves the spread of the primary tumor to other body organs. As much as the early detection of cancer is essential, the timely detection of metastasis, the identification of biomarkers, and treatment choice are valuable for improving the quality of life for metastatic cancer patients. This study reviews the existing studies on classical machine learning (ML) and deep learning (DL) in metastatic cancer research. Since the majority of metastatic cancer research data are collected in the formats of PET/CT and MRI image data, deep learning techniques are heavily involved. However, its black-box nature and expensive computational cost are notable concerns. Furthermore, existing models could be overestimated for their generality due to the non-diverse population in clinical trial datasets. Therefore, research gaps are itemized; follow-up studies should be carried out on metastatic cancer using machine learning and deep learning tools with data in a symmetric manner.

Study on Sgc8 Aptamer-mediated Nucleic Acid Nanomaterial-doxorubicin Complex for Tumor Targeted Therapy

Chemotherapy is one of the most important treatments for malignant cancers, but most chemotherapeutic drugs are poorly targeted, highly toxic and expensive, resulting in unsatisfactory treatment results for cancer patients. Therefore, intelligent drug delivery platforms are needed to be explored urgently to enhance drug treatment and reduce toxicity on normal cells. Nucleic acid nanomaterials are a class of nanomaterials developed on the basis of the "base complementary pairing principle", which have the advantages of good programmability, high stability, good biocompatibility, and strong targeting. Herein, we present a simple Sgc8 aptamer-modified nucleic acid nanomaterial (Sgc8NM) for the targeted delivery of Doxorubicin (Dox), a widely used chemotherapy drug in clinic. Studies have shown the Sgc8NM-Dox performed a precise treatment effect on target cells and low toxicity on non-target cells, providing a new strategy for the potential application of nanocomposite drugs in targeted cancer delivery.

Long-term excess mortality and net survival among elderly diffuse large B-cell lymphoma patients after front-line R-CHOP treatment

In the era of immunochemotherapy, data on the long-term prognosis of elderly patients diagnosed with a diffuse large B-cell lymphoma (DLBCL) are scarce. In this population and on the longer term, other-cause mortality is an important competing risk that needs to be accounted for. Using clinical trial data and relative survival approaches, we estimated the 10-year net survival (NS) and we described the excess mortality hazard (EMH) due (directly or indirectly) to the DLBCL, over time and according to main prognosis factors using flexible regression modelling. The 10-year NS was 65% [59; 71]. Using the flexible modelling, we showed that the EMH decreases steeply after diagnosis. The variables 'performance status', 'number of extra-nodal sites' and the serum 'lactate dehydrogenase' were strongly associated with the EMH, even after adjustment on other important variables. EMH is very close to zero at 10 years for the whole population, so DLBCL patients do not experience an increased mortality compared to the general population in the long term. The number of extra-nodal sites was an important prognostic factor shortly after diagnosis, suggesting that it is correlated with an important but unmeasured prognostic factor that would lead to this selection effect over time.

Co-Design and Validation of a Family Nursing Educational Intervention in Long-Term Cancer Survivorship Using Expert Judgement

The number of cancer survivors is increasing exponentially thanks to early screening, treatment, and cancer care. One of the main challenges for healthcare systems and professionals is the care of cancer survivors and their families, as they have specific needs that are often unmet. Nursing students, as future healthcare professionals, need education to face these new health demands. They will need to develop specific competencies to help them care for and empower this emerging population. The aim of the study was to co-design and validate an educational intervention on long-term cancer survivorship for nursing, through a multidisciplinary panel of experts. Group interviews were conducted with a panel of 11 experts, including eight professionals from different backgrounds (oncology, cancer nursing, pharmacology, and education), a long-term cancer survivor, a family member of a cancer survivor, and a nursing student. The experts validated a pioneer educational intervention to train nursing students in long-term cancer survival. The co-design and validation of the intervention from an interdisciplinary perspective and with the participation of long-term cancer survivors and their families was considered relevant as it included the vision of all the stakeholders involved in long-term cancer survivorship.

Smedby K, Eloranta S. Patient trajectories after diagnosis of diffuse large B-cell lymphoma-a multistate modelling approach to estimate the chance of lasting remission

BACKGROUND

Achieving lasting remission for at least 2 years is a good indicator for favourable prognosis long term after Diffuse large B-cell lymphoma (DLBCL). The aim of this study was to provide real-world probabilities, useful in risk communication and clinical decision-making, of the chance for lasting remissions by clinical characteristics.

METHODS

DLBCL patients in remission after primary treatment recorded in the Swedish Lymphoma register 2007-2014 (n = 2941) were followed for relapse and death using multistate models to study patient trajectories. Flexible parametric models were used to estimate transition rates.

RESULTS

At 2 years, 80.7% (95% CI: 79.0-82.2) of the patients were predicted to remain in remission and 13.2% (95% CI: 11.9-14.6) to have relapsed. The relapse risk peaked at 7 months, and the annual decline of patients in remission stabilised after 2 years. The majority of patients in the second remission transitioned into a new relapse. The probability of a lasting remission was reduced by 20.4% units for patients with IPI 4-5 compared to patients with IPI 0-1, and time in remission was shortened by 3.5 months.

CONCLUSION

The long-term prognosis was overall favourable with 80% achieving durable first remissions. However, prognosis varied by clinical subgroups and relapsing patients seldom achieved durable second remissions.

Theory and Practice of Integrating Machine Learning and Conventional Statistics in Medical Data Analysis

The practice of medical decision making is changing rapidly with the development of innovative computing technologies. The growing interest of data analysis with improvements in big data computer processing methods raises the question of whether machine learning can be integrated with conventional statistics in health research. To help address this knowledge gap, this paper presents a review on the conceptual integration between conventional statistics and machine learning, focusing on the health research. The similarities and differences between the two are compared using mathematical concepts and algorithms. The comparison between conventional statistics and machine learning methods indicates that conventional statistics are the fundamental basis of machine learning, where the black box algorithms are derived from basic mathematics, but are advanced in terms of automated analysis, handling big data and providing interactive visualizations. While the nature of both these methods are different, they are conceptually similar. Based on our review, we conclude that conventional statistics and machine learning are best to be integrated to develop automated data analysis tools. We also strongly believe that machine learning could be explored by health researchers to enhance conventional statistics in decision making for added reliable validation measures.

Web-Based Personalized Intervention to Improve Quality of Life and Self-Efficacy of Long-Term Breast Cancer Survivors: Study Protocol for a Randomized Controlled Trial

Long-term breast cancer survivors (>5 years free of disease) may suffer late sequelae of cancer that impact on their quality of life. The use of telehealth for cancer care is recommended but little is known about the effectiveness of digital interventions for long-term cancer survivors. This study aims to evaluate the effectiveness of a web-based personalized intervention based on artificial intelligence instead of usual primary health care to improve the quality of life of long-term survivors of breast cancer and self-efficacy for the management of late sequelae. A randomized controlled trial will be conducted. The sample will consist of long-term breast cancer survivors recruited from primary health centers. Women will be randomly assigned to the intervention group to receive a web-based personalized intervention or to the control group to receive standard primary health care by nurses. Data on quality of life of cancer survivors and self-efficacy for the management of late sequelae of cancer will be collected and assessed at preintervention, and at 3, 6, and 9 months. It is expected that, at the end of the programme, the experimental group will have improved quality of life and improved self-efficacy for the management of late sequelae of cancer.

Quantifying the number of deaths among Aboriginal and Torres Strait Islander cancer patients that could be avoided by removing survival inequalities, Australia 2005–2016

Background

While Aboriginal and Torres Strait Islander peoples have poorer cancer survival than other Australians, absolute measures of survival disparities are lacking. This study quantified crude probabilities of deaths from cancer and other causes and estimated the number of avoidable deaths for Aboriginal and Torres Strait Islanders if these survival disparities were removed.

Methods

Flexible parametric relative survival models were used to estimate reported measures for a population-based cohort of 709,239 Australians (12,830 Aboriginal and Torres Strait Islander peoples), 2005–2016.

Results

Among Aboriginal and Torres Strait Islander peoples, the 5-year crude probability of cancer death was 0.44, while it was 0.07 for other causes of death. These probabilities were 0.07 and 0.03 higher than among other Australians, respectively. Magnitude of these disparities varied by cancer type and ranged for cancer deaths from <0.05 for pancreatic, prostate and uterine cancers to 0.20 for cervical and head and neck cancers. Values for disparity in other causes of death were generally lower. Among an average cohort of Aboriginal and Torres Strait Islander peoples diagnosed per year over the most recent five-year diagnosis period (2012–2016, n = 1,269), approximately 133 deaths within 5 years of diagnosis were potentially avoidable if they had the same overall survival as other Australians, with 94 of these deaths due to cancer. The total number of avoided deaths over the entire study period (2005–2016) was 1,348, with 947 of these deaths due to cancer.

Conclusions

Study findings suggest the need to reduce the prevalence of risk factors prevalence, increase screening participation, and improve early detection, diagnosis and treatment rates to achieve more equitable outcomes for a range of cancer types. Reported measures provide unique insights into the impact of a cancer diagnosis among Aboriginal and Torres Strait Islander peoples from a different perspective to standard relative survival measures.

Health status of prevalent cancer cases as measured by mortality dynamics (cancer vs. noncancer): Application to five major cancers sites

BACKGROUND

Cancer prevalence is heterogeneous because it includes individuals who are undergoing initial treatment and those who are in remission, experiencing relapse, or cured. The proposed statistical approach describes the health status of this group by estimating the probabilities of death among prevalent cases. The application concerns colorectal, lung, breast, and prostate cancers and melanoma in France in 2017.

METHODS

Excess mortality was used to estimate the probabilities of death from cancer and other causes.

RESULTS

For the studied cancers, most deaths from cancer occurred during the first 5 years after diagnosis. The probability of death from cancer decreased with increasing time since diagnosis except for breast cancer, for which it remained relatively stable. The time beyond which the probability of death from cancer became lower than that from other causes depended on age and cancer site: for colorectal cancer, it was 6 years after diagnosis for women (7 years for men) aged 75-84 and 20 years for women (18 years for men) aged 45-54 years, whereas cancer was the major cause of death for women younger than 75 years whatever the time since diagnosis for breast and for all patients younger than 75 years for lung cancer. In contrast, deaths from other causes were more frequent in all the patients older than 75 years. Apart from breast cancer in women younger than 55 years and lung cancer in women older than 55 years and men older than 65 years, the probability of death from cancer among prevalent cases fell below 1%, with varying times since diagnosis.

CONCLUSIONS

The authors' approach can be used to better describe the burden of cancer by estimating outcomes in prevalent cases.

Downregulation of lncRNA ASMTL-AS1 in Epithelial Ovarian Cancer Correlates with Worse Prognosis and Cancer Progression

Given the characters of "Silent killer", epithelial ovarian cancer (EOC) usually suffered late diagnosis and poor prognosis. Therefore, this study aimed to explore the prognostic significance of ASMTL-AS1 in EOC and investigated the effect of lncRNA ASMTL-AS1 dysregulation on tumor cellular function. ASMTL-AS1 expression was analyzed in 133 EOC tissues and five kinds of cell lines by RT-qPCR. The expression of ASMTL-AS1 was tested for correlation with clinical data using the chi-square test and clinical follow-up using Kaplan-Meier method with log-rank test. Further, the prognostic parameters in predicting EOC overall survival were assessed by using multivariate Cox proportional hazards analysis. In vitro assays, including MTT assay and transwell assay, were conducted using EOC cell lines with overexpression of ASMTL-AS1. In tumorous tissues and cell lines, ASMTL-AS1 was lowly expressed compared with normal ones. This downregulation was associated with the advanced FIGO stage, positive ascites cytology, and lymph node. In particular, low levels of ASMTL-AS1 were revealed to have a high prognostic impact on EOC. ASMTL-AS1 overexpression strongly decreased cell proliferation, migration, and invasion in vitro partly by moderating miR-1228-3p. This study demonstrates a significant role for lowly expressed ASMTL-AS1 in EOC allowing for the prediction of prognosis for EOC. Considering that ASMTL-AS1 is strongly involved in cell growth and invasion, ASMTL-AS1 may be a promising marker for EOC prognosis and therapy.

Reference adjusted loss in life expectancy for population-based cancer patient survival comparisons - with an application to colon cancer in Sweden

BACKGROUND

The loss in life expectancy, LLE, is defined as the difference in life expectancy between cancer patients and that of the general population. It is a useful measure for summarising the impact of a cancer diagnosis on an individual's life expectancy. However, it is less useful for making comparisons of cancer survival across groups or over time, since the LLE is influenced by both mortality due to cancer and other causes and the life expectancy in the general population.

METHODS

We present an approach for making LLE estimates comparable across groups and over time by using reference expected mortality rates with flexible parametric relative survival models. The approach is illustrated by estimating temporal trends in LLE of colon cancer patients in Sweden.

RESULTS

The life expectancy of Swedish colon cancer patients has improved, but the LLE has not decreased to the same extent since the life expectancy in the general population has also increased. When using a fixed population and other-cause mortality, i.e. a reference-adjusted approach, the LLE decreases over time. For example, using 2010 mortality rates as the reference, the LLE for females diagnosed at age 65 decreased from 11.3 if diagnosed in 1976 to 7.2 if diagnosed in 2010, and from 3.9 to 1.9 years for women 85 years old at diagnosis.

CONCLUSION

The reference-adjusted LLE is useful for making comparisons across calendar time, or groups, since differences in other cause mortality are removed.

IMPACT

The reference-adjusted approach enhances the use of LLE as a comparative measure.

Quantifying Differences in Remaining Life Expectancy after Cancer Diagnosis, Aboriginal and Torres Strait Islanders, and Other Australians, 2005-2016

BACKGROUND

This study quantified differences in remaining life expectancy (RLE) among Aboriginal and Torres Strait Islander and other Australian patients with cancer. We assessed how much of this disparity was due to differences in cancer and noncancer mortality and calculated the population gain in life years for Aboriginal and Torres Strait Islanders cancer diagnoses if the cancer survival disparities were removed.

METHODS

Flexible parametric relative survival models were used to estimate RLE by Aboriginal and Torres Strait Islander status for a population-based cohort of 709,239 persons (12,830 Aboriginal and Torres Strait Islanders), 2005 to 2016.

RESULTS

For all cancers combined, the average disparity in RLE was 8.0 years between Aboriginal and Torres Strait Islanders (12.0 years) and other Australians (20.0 years). The magnitude of this disparity varied by cancer type, being >10 years for cervical cancer versus <2 years for lung and pancreatic cancers. For all cancers combined, around 26% of this disparity was due to differences in cancer mortality and 74% due to noncancer mortality. Among 1,342 Aboriginal and Torres Strait Islanders diagnosed with cancer in 2015 an estimated 2,818 life years would be gained if cancer survival disparities were removed.

CONCLUSIONS

A cancer diagnosis exacerbates the existing disparities in RLE among Aboriginal and Torres Strait Islanders. Addressing them will require consideration of both cancer-related factors and those contributing to noncancer mortality.

IMPACT

Reported survival-based measures provided additional insights into the overall impact of cancer over a lifetime horizon among Aboriginal and Torres Strait Islander peoples.

Modulation of the immune system by melatonin; implications for cancer therapy

Immune system interactions within the tumour have a key role in the resistance or sensitization of cancer cells to anti-cancer agents. On the other hand, activation of the immune system in normal tissues following chemotherapy or radiotherapy is associated with acute and late effects such as inflammation and fibrosis. Some immune responses can reduce the efficiency of anti-cancer therapy and also promote normal tissue toxicity. Modulation of immune responses can boost the efficiency of anti-tumour therapy and alleviate normal tissue toxicity. Melatonin is a natural body agent that has shown promising results for modulating tumour response to therapy and also alleviating normal tissue toxicity. This review tries to focus on the immunomodulatory actions of melatonin in both tumour and normal tissues. We will explain how anti-cancer drugs may cause toxicity for normal tissues and how tumours can adapt themselves to ionizing radiation and anti-cancer drugs. Then, cellular and molecular mechanisms of immunoregulatory effects of melatonin alone or combined with other anti-cancer agents will be discussed.

Long non-coding RNA H19X promotes tumorigenesis and metastasis of colorectal cancer through regulating the miR-503-5p/KANK1 axis

BACKGROUND

It has been well established that the long non-coding RNAs (lncRNAs) plays a critical role in tumor progression. However, the function of these transcripts and mechanisms responsible for their deregulation in colorectal cancer (CRC) remain to be investigated.

OBJECTIVE

To explore the potential effect and regulation mechanism of lncRNA H19X in colorectal cancer.

METHODS

We predicted and validated long non-coding RNA H19X from microarray data of colorectal cancer tissues. In addition, the biological behaviors of H19X and miR-503-5p on CRC were examined in vitro and in vivo, including MTT, colony formation assay, Hoechst33342 and transwell assay. The mRNA and protein levels of KN Motif and Ankyrin Repeat Domains 1 (KANK1) were analyzed by Quantitative real-time PCR (qRT-PCR), western blotting (WB) assay. Moreover, bioinformatics tools and dual-luciferase reporter assay were applied to demonstrate the relationship between KANK1 and miR-503-5p.

RESULTS

H19X was remarkably up-regulated in CRC tissues. Its expression related to tumor size (p = 0.041), lymph node metastasis (p = 0.037), distal metastasis (p = 0.028), advanced TNM stage (p = 0.034) and poor survival in CRC. H19X acted as an oncogenic lncRNA that induced CRC cell proliferation, invasion and metastasis. Through a number of functional studies, we found that H19X silencing inhibited the malignance phenotype of cancer cells through loss of miR-503-5p. Further studies demonstrated that miR-503-5p was involved in the progression of CRC by directly regulating the downstream target KANK1.

CONCLUSION

Collectively, the findings of the present study indicate H19X/miR-503-5p/KANK1 axis has critical role in the progression of colorectal cancer, providing an effective prognostic indicator and promising target in treatment of colorectal cancer.

[Пятилетнее исследование влияния кардиомониторинга на общую выживаемость больных хроническим лимфолейкозом, получающих таргетную терапию ибрутинибом]

Aim      To evaluate the effect of cardiac monitoring on overall survival of patients with chronic lymphoid leukosis (CLL) on targeted therapy with ibrutinib.Material and methods  Survival of oncological patients depends not only on the efficacy of the antitumor therapy. Cardiovascular comorbidities and emerging cardiotoxicity of the antitumor treatment can considerably impair the quality and duration of patients' life. The problem of the need for regular cardiological monitoring of oncological patients remains unsolved. A prospective 5-year study was performed that included cardiological monitoring of patients with CLL on chronic targeted therapy with ibrutinib, the side effects of which include atrial fibrillation (AF) and arterial hypertension (AH). The study included 217 patients aged 66.0 [32.0; 910.] years; 144 of them were men aged 66.0 [32.0; 91.0] years and 83 were women aged 65.0 [39.0; 83.0] years. Electrocardiography and echocardiography, evaluation of comorbidity with the Charlson's index, and evaluation of frailty with the Geriatric 8 questionnaire and the Groningen Frailty Index were performed repeatedly for all patients. In the active cardiac monitoring group (n=89), besides the standard evaluation, active medical monitoring of symptoms and general well-being, blood pressure (BP) and pulse rate, monitoring of cardioprotective drug intake and correction, if necessary, and calling patients for examination and additional evaluation were performed every week. The remaining 128 patients were evaluated repeatedly but did not maintain the remote monitoring with messengers; they constituted a standard follow-up group.Results This was a study of overall survival of patients with CLL on targeted therapy with ibrutinib depending on the cardiac monitoring program. The age of patients did not differ in the active cardiac monitoring group and the standard follow-up group (66.0 [60.0; 70.0] and 66.0 [59.0; 74.0] years, respectively). The active cardiac monitoring group contained somewhat more men than the standard follow-up group (68.8 and 53.9 %, respectively; р=0.026). At baseline, the groups did not differ in the number of pretreatment lines, frailty test results (Geriatric 8 questionnaire, Groningen Frailty Index), comorbidity (Charlson's index), and echocardiographic data. The active cardiac monitoring group contained more patients with AH (р&lt;0.0001), with AF (р&lt;0.0001), patients receiving anticoagulants (р&lt;0.0001), and a comparable number of patients with ischemic heart disease. In the active cardiac monitoring group, 70 (90.9%) of 77 patients with CLL and AH achieved goal BP whereas in the standard follow-up group, 26 (39.9 %) of 66 (р&lt;0.0001) patients achieved the BP goal, regardless of whether their elevated BP developed before or during the ibrutinib treatment. This group contained significantly more patients who required cardiac surgical intervention (coronary stenting, pacemaker implantation), 12 vs. 0 in the standard follow-up group (р=0.0004). The overall 5-year survival was significantly higher for patients of the active cardiac monitoring group, both for men (р&lt;0.0001) and women (р&lt;0.0001) with CLL, including patients older than 70 years (р=0.0004), CLL patients with a median pretreatment line number of 1 (р&lt;0.0001), patients with a median chemotherapy line number of 4 (р&lt;0.0001), and patients with genetic abnormalities (р=0.004) pretreated with fludarabine and/or anthracyclines (р&lt;0.0001). The Cox regression analysis showed that the strongest predictor of survival was the achievement of stable goal BP in CLL patients with AH during the continuous cardiac monitoring. Despite more pronounced cardiac comorbidity, CLL patients on the active cardiac monitoring group showed a longer survival than patients on the standard follow-up. Thus, mean survival time of deceased CLL patients who had been on the cardiac monitoring was 36.1 months vs. 17.5 months (р&lt;0.0001) for patients who had been on the standard follow-up.Conclusion      The study has demonstrated the prognostic significance of continuous participation of a cardiologist in managing onco-hematological patients. CLL patients on the active cardiac monitoring, the regular pattern of which was provided by the remote control, had a significantly higher overall survival compared to patients who visited a cardiologist periodically. A significant predomination of patients with CLL and AH who achieved stable goal BP, continuous monitoring of anticoagulant dosing in patients with AF in that group, and early detection and correction of cardiovascular complications can explain the highly significant difference in the 5-year survival between CLL patients on chronic targeted ibrutinib treatment with different cardiac monitoring programs (р&lt;0.0001). The active cardiac monitoring with remote control allows achievement of a higher 5-year overall survival of CLL patients receiving ibrutinib (p&lt;0.0001).

LncRNA PCAT1 activates SOX2 and suppresses radioimmune responses via regulating cGAS/STING signalling in non-small cell lung cancer

Background

The expression of long non‐coding RNA (lncRNA) prostate cancer‐associated ncRNA transcripts 1 (PCAT1) is increased in non‐small cell lung cancer (NSCLC). It stimulates tumour growth and metastasis, but its role in the radioimmune responses remain unknown. We aimed to explore the impacts of PCAT1 on tumorigenesis and radioimmune responses and the underlying molecular mechanisms in NSCLC.

Methods

Comprehensive bioinformatics analysis was performed to identify immunosuppressive lncRNAs involved with tumour invasion in NSCLC. The expression levels of PCAT1 were analysed by in situ hybridisation in 55 paired NSCLC tissues and adjacent normal tissues. Both loss‐ and gain‐of‐function assays were performed to examine the effects of PCAT1 and SOX2 on NSCLC cell behaviours in vivo and in vitro. Bioinformatic analyses, chromatin isolation by RNA purification (ChIRP) and dual‐luciferase reporter assays were applied to validate the regulatory effects of PCAT1 on SOX2 expression. Chromatin immunoprecipitation, luciferase and rescue assays were utilised to identify the relationship between SOX2 and the cGAS/stimulator of interferon genes (STING) signalling.

Results

PCAT1 was immunosuppressive and related with NSCLC invasion. Increased PCAT1 was negatively correlated with immune cell infiltration in NSCLC. PCAT1 knockdown restrained proliferation, increased apoptosis, and repressed cell metastasis in vivo and in vitro. PCAT1 activated SOX2 that accelerated tumorigenesis and immunosuppression. SOX2 promoted tumour growth through inhibiting cytotoxic T‐cell immunity. Moreover, SOX2 restrained cGAS transcription and hampered downstream type I interferon (IFN)‐induced immune responses. Inhibition of PCAT1/SOX2 in collaboration with radiation further inhibited tumour growth, and initiated the cGAS/STING signalling pathway, which enhanced the immune responses of radiotherapy in NSCLC.

Conclusions

PCAT1/SOX2 axis promoted tumorigenesis and immunosuppression through inhibition of cGAS/STING signalling‐mediated T‐cell activation. Inhibition of PCAT1 and SOX2 synergised with radiotherapy to activate the immune response and could serve as potential therapeutic targets.

Application of Proteomics in the Discovery of Radiosensitive Cancer Biomarkers

Radiation therapy remains an important component of cancer treatment. Gene-encoded proteins were the actual executors of cellular functions. Proteomic was a novel technology that can systematically analysis protein composition and measure their levels of change, this was a high throughput method, and were the import tools in the post genomic era. In recent years, rapid progress of proteomic have been made in the study of cancer mechanism, diagnosis, and treatment. This article elaborates current advances and future directions of proteomics in the discovery of radiosensitive cancer biomarkers.

ANXA2P2: A Potential Immunological and Prognostic Signature in Ovarian Serous Cystadenocarcinoma via Pan-Carcinoma Synthesis

Background

Although the effect of pseudogene ANXA2P2 on some tumors has been reported in a few literatures, the therapeutic potential and prognostic value of ANXA2P2 in ovarian serous cystadenocarcinoma (OV) have not been elucidated.

Methods

The correlation for ANXA2P2 expression patterns to prognostic characteristics, tumor immune microenvironment, immune cell infiltration level, tumor mutation burden (TMB), tumor microsatellite instability (MSI), drug sensitivity, and pathway function enrichment were investigated in pan-carcinoma via TCGA and GTEx databases. Subsequently, the role of ANXA2P2 expression levels in the pathway enrichments and prognosis prediction in OV were further explored using weighted correlation network analysis (WGCNA) analysis, gene mutation analysis, and risk-independent prognostic analysis.

Results

ANXA2P2 was frequently overexpressed in a variety of tumors compared with normal tissues. The correlation analysis for prognostic characteristics, tumor immune microenvironment, immune cell infiltration level, TMB, MSI, drug sensitivity, and pathway function enrichment revealed that ANXA2P2 expression patterns might deal a significant impact on the pathogenesis, development, and prognosis of various tumors. Then, GSVA, GSEA, WGCNA, gene mutation, and independent prognostic analysis for OV have indicated that high expression in ANXA2P2 could be mostly enriched in TNF-α signaling-via-NF-κB, epithelial-mesenchymal transition, apical junction, IL-6-JAK STAT3 signaling, etc., which were also proved to act as crucial factors on tumorigenesis, development, invasion, and metastasis. The mutation of TP53 (94%), TTN (24%), and CSMD3 (9%) in the biological process of tumor had been confirmed by relevant studies. Finally, the independent prognostic analysis demonstrated that ANXA2P2 expression in OV contributes greatly to the dependability of 3- and 5-year survival prediction.

Conclusion

In summary, our findings might provide a helpful foundation for prospective explorative researches, afford new strategies for the clinical treatment, deal prognosis prediction, and give new hope for OV patients.

Assessing lead time bias due to mammography screening on estimates of loss in life expectancy

BACKGROUND

An increasingly popular measure for summarising cancer prognosis is the loss in life expectancy (LLE), i.e. the reduction in life expectancy following a cancer diagnosis. The proportion of life lost (PLL) can also be derived, improving comparability across age groups as LLE is highly age-dependent. LLE and PLL are often used to assess the impact of cancer over the remaining lifespan and across groups (e.g. socioeconomic groups). However, in the presence of screening, it is unclear whether part of the differences across population groups could be attributed to lead time bias. Lead time is the extra time added due to early diagnosis, that is, the time from tumour detection through screening to the time that cancer would have been diagnosed symptomatically. It leads to artificially inflated survival estimates even when there are no real survival improvements.

METHODS

In this paper, we used a simulation-based approach to assess the impact of lead time due to mammography screening on the estimation of LLE and PLL in breast cancer patients. A natural history model developed in a Swedish setting was used to simulate the growth of breast cancer tumours and age at symptomatic detection. Then, a screening programme similar to current guidelines in Sweden was imposed, with individuals aged 40-74 invited to participate every second year; different scenarios were considered for screening sensitivity and attendance. To isolate the lead time bias of screening, we assumed that screening does not affect the actual time of death. Finally, estimates of LLE and PLL were obtained in the absence and presence of screening, and their difference was used to derive the lead time bias.

RESULTS

The largest absolute bias for LLE was 0.61 years for a high screening sensitivity scenario and assuming perfect screening attendance. The absolute bias was reduced to 0.46 years when the perfect attendance assumption was relaxed to allow for imperfect attendance across screening visits. Bias was also present for the PLL estimates.

CONCLUSIONS

The results of the analysis suggested that lead time bias influences LLE and PLL metrics, thus requiring special consideration when interpreting comparisons across calendar time or population groups.

Ferroptosis triggered by dihydroartemisinin facilitates chlorin e6 induced photodynamic therapy by inhibiting GPX4 and enhancing ROS

Photodynamic therapy (PDT) is noninvasive, low toxicity, and photo-selective, but may be resisted by malignant cells. A previous study found chlorin e6 (Ce6) mediated PDT showed drug resistance in lung cancer cells (LLC), which may be associated with PDT-induced DNA damage response (DDR). DDR may up-regulate glutathione peroxidase 4 (GPX4), which in turn degrade ROS induced by PDT. However, dihydroartemisinin (DHA) was found to down-regulate GPX4. Accordingly, the DHA was hypothesized to improve the resistance to PDT. The present work explores the mechanism of Ce6 mediated drug resistance and reveals whether DHA can enhance the efficacy of PDT by suppressing GPX4. The in vitro experiments found Ce6 treatment did not inhibit the viability of LLC within 6 hr without inducing significant apoptosis, suggesting LLC were resistant to PDT. Further investigation demonstrated PDT could damage DNA and up-regulate GPX4, thus degrading the generated ROS. DHA effectively inhibited the viability of LLC and induced apoptosis. Importantly, DHA displayed a prominent inhibitory effect on the GPX4 expression and thereby triggered ferroptosis. Combining DHA with Ce6 for treatment of LLC resulted in the suppressed GPX4 and elevated ROS. Finally, the findings showed DHA combined with Ce6 exhibited superb anti-lung cancer efficacy. In summary, Ce6 PDT damages DNA, up-regulates GPX4 to degrade ROS, thereby inducing drug resistance. Down-regulation of GPX4 by DHA-triggered ferroptosis significantly enhances the efficacy of PDT. This study provides an outstanding theoretical basis for the regulation of the intratumoral redox system and improving PDT efficacy against lung cancer by herbal monomer DHA.

Survival Trends of Right- and Left-Sided Colon Cancer across Four Decades: A Norwegian Population-Based Study

BACKGROUND

Patients with right-sided colon cancer (RCC) and left-sided colon cancer (LCC) differ clinically and molecularly. The main objective was to investigate stage-stratified survival and recurrence of RCC and LCC across four 10-year periods.

METHODS

Patients diagnosed from 1977 to 2016 with colon adenocarcinoma were included from the Cancer Registry of Norway. Primary tumor location (PTL) was defined as RCC if proximal and LCC if distal to the splenic flexure. Multivariable regressions were used to estimate HRs for overall survival (OS), recurrence-free survival (RFS), survival after recurrence (SAR), and excess HRs (eHR) for relative survival (RS).

RESULTS

72,224 patients were eligible for analyses [55.1% (n = 39,769/72,224) had RCC]. In 1977 to 1986, there was no difference between LCC and RCC in OS [HR, 1.01; 95% confidence interval (CI), 0.97-1.06; P = 0.581] or RS (eHR, 0.96; 95% CI, 0.90-1.02; P = 0.179). In 2007 to 2016, LCC had significantly better OS (HR, 0.84; 95% CI, 0.80-0.87; P < 0.001) and RS (eHR, 0.76; 95% CI, 0.72-0.81; P < 0.001) compared with RCC. The gradually diverging and significantly favorable prognosis for LCC was evident for distant disease across all time periods and for regional disease from 2007 onward. There was no difference in RFS between LCC and RCC in patients less than 75 years during 2007 to 2016 (HR, 0.99; 95% CI, 0.91-1.08; P = 0.819); however, SAR was significantly better for LCC (HR, 0.61; 95% CI, 0.53-0.71; P < 0.001).

CONCLUSIONS

A gradually diverging and increasingly favorable prognosis was observed for patients with LCC with advanced disease over the past four decades.

IMPACT

Current PTL survival disparities stress the need for further exploring targetable molecular subgroups across and within different PTLs to further improve patient outcomes.

Development and Validation of Genome Instability-Associated lncRNAs to Predict Prognosis and Immunotherapy of Patients With Hepatocellular Carcinoma

The pathophysiology of hepatocellular carcinoma (HCC) is prevalently related to genomic instability. However, research on the association of extensive genome instability lncRNA (GILnc) with the prognosis and immunotherapy of HCC remains scarce. We placed the top 25% of somatic mutations into the genetically unstable group and placed the bottom 25% of somatic mutations into the genetically stable group, and then to identify different expression of GILnc between the two groups. Then, LASSO was used to identify the most powerful prognostic GILnc, and a risk score for each patient was calculated according to the formula. Based on a computational frame, 245 different GILncs in HCC were identified. An eight GILnc model was successfully established to predict overall survival in HCC patients based on LASSO, then we divided HCC patients into high-risk and low-risk groups, and a significantly shorter overall survival in the high-risk group was observed compared to those in the low-risk group, and this was validated in GSE76427 and Tongji cohorts. GSEA revealed that the high-risk group was more likely to be enriched in cancer-specific pathways. Besides, the GILnc signature has greater prognostic significance than TP53 mutation status alone, and it is capable of identifying intermediate subtype groups existing with partial TP53 functionality in TP53 wild-type patients. Importantly, the high-risk group was associated with the therapeutic efficacy of PD-L1 blockade, suggesting that the development of potential drugs targeting these GILnc could aid the clinical benefits of immunotherapy. Finally, the GILnc signature model is better than the prediction performance of two recently published lncRNA signatures. In summary, we applied bioinformatics approaches to suggest that an eight GILnc model could serve as prognostic biomarkers to provide a novel direction to explore the pathogenesis of HCC.

LncRNA ASMTL-AS1/microRNA-1270 differentiate prognostic groups in gastric cancer and influence cell proliferation, migration and invasion

The objective of this study was to determine the expression levels of ASMTL-AS1 and miR-1270 in gastric cancer, and to explore whether ASMTL-AS1 and miR-1270 is associated with cancer prognosis and progression or not. ASMTL-AS1 and miR-1270 expression were quantified in gastric cancer tissues and adjacent normal tissues (n = 167) and cell lines. The potential of ASMTL-AS1 and miR-1270 as prognostic biomarkers was evaluated by the receiver operating characteristic (ROC) curve, Kaplan-Meier, and multivariate Cox regression analyses. The binding between ASMTL-AS1 and miR-1270 was verified by the Luciferase reporter assay and RNA pull-down assay. Functional roles of ASMTL-AS1/miR-1270 on cells were investigated in HGC-27 and NCI-N87 cells by MTS viability, Transwell migration, and Matrigel invasion assay. ASMTL-AS1 was significantly downregulated while miR-1270 was upregulated in gastric cancer tissues as compared with normal tissue and cell lines. According to the studies, ASMTL-AS1 and miR-1270 were related to unfavorable clinical parameters, such as the advanced TNM stage. Downregulated ASMTL-AS1 and upregulated miR-1270 were associated with reduced 5-year overall survival. Functional studies suggested that ASMTL-AS1 inhibits proliferation, migration, and invasion of HGC-27 and NCI-N87 cells by regulation of miR-1270. In summary, ASMTL-AS1 and miR-1270 are associated with poor prognosis of patients with gastric cancer. ASMTL-AS1 inhibited gastric cancer progression by regulating miR-1270. Therefore, ASMTL-AS1/miR-1270 may be a potential prognostic biomarker and novel strategy for gastric cancer targeted therapy.

The evolution of the loss of life expectancy in patients with chronic myeloid leukaemia: a population-based study in the Netherlands, 1989-2018

Studies on the conditional life expectancy of patients with chronic myeloid leukaemia (CML) are lacking. Using data from the Netherlands Cancer Registry, we examined the life expectancy of patients with CML in the Netherlands diagnosed during 1989-2018. As of the early 2010s, the life expectancy of patients with CML who survived several years after diagnosis came narrowly close to the general population's life expectancy, regardless of age. This finding can essentially be ascribed to the introduction and broader application of tyrosine kinase inhibitors (TKIs) and provide optimism to patients with CML who can look forward to a near-normal life expectancy in a modern TKI era.

Artificial Intelligence Combined With Big Data to Predict Lymph Node Involvement in Prostate Cancer: A Population-Based Study

Background

A more accurate preoperative prediction of lymph node involvement (LNI) in prostate cancer (PCa) would improve clinical treatment and follow-up strategies of this disease. We developed a predictive model based on machine learning (ML) combined with big data to achieve this.

Methods

Clinicopathological characteristics of 2,884 PCa patients who underwent extended pelvic lymph node dissection (ePLND) were collected from the U.S. National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. Eight variables were included to establish an ML model. Model performance was evaluated by the receiver operating characteristic (ROC) curves and calibration plots for predictive accuracy. Decision curve analysis (DCA) and cutoff values were obtained to estimate its clinical utility.

Results

Three hundred and forty-four (11.9%) patients were identified with LNI. The five most important factors were the Gleason score, T stage of disease, percentage of positive cores, tumor size, and prostate-specific antigen levels with 158, 137, 128, 113, and 88 points, respectively. The XGBoost (XGB) model showed the best predictive performance and had the highest net benefit when compared with the other algorithms, achieving an area under the curve of 0.883. With a 5%~20% cutoff value, the XGB model performed best in reducing omissions and avoiding overtreatment of patients when dealing with LNI. This model also had a lower false-negative rate and a higher percentage of ePLND was avoided. In addition, DCA showed it has the highest net benefit across the whole range of threshold probabilities.

Conclusions

We established an ML model based on big data for predicting LNI in PCa, and it could lead to a reduction of approximately 50% of ePLND cases. In addition, only ≤3% of patients were misdiagnosed with a cutoff value ranging from 5% to 20%. This promising study warrants further validation by using a larger prospective dataset.

Promising Advances in LINC01116 Related to Cancer

Long non-coding RNAs (lncRNAs) are RNAs with a length of no less than 200 nucleotides that are not translated into proteins. Accumulating evidence indicates that lncRNAs are pivotal regulators of biological processes in several diseases, particularly in several malignant tumors. Long intergenic non-protein coding RNA 1116 (LINC01116) is a lncRNA, whose aberrant expression is correlated with a variety of cancers, including lung cancer, gastric cancer, colorectal cancer, glioma, and osteosarcoma. LINC01116 plays a crucial role in facilitating cell proliferation, invasion, migration, and apoptosis. In addition, numerous studies have recently suggested that LINC01116 has emerged as a novel biomarker for prognosis and therapy in malignant tumors. Consequently, we summarize the clinical significance of LINC01116 associated with biological processes in various tumors and provide a hopeful orientation to guide clinical treatment of various cancers in future studies.

Improving resistance training prescription through the load-velocity relationship in breast cancer survivors: The case of the leg-press exercise

The aims of this study were: (i) to analyse the load-velocity relationship in the bilateral leg-press exercise in female breast cancer survivors, (ii) to assess whether mean velocity (MV) or peak velocity (PV) show stronger relationship with the relative load, and (iii) to examine whether linear (LA) or polynomic (PA) adjustment predict the velocities associated with each %1RM with greater precision. Twenty-two female breast cancer survivors (age: 50.2 ± 10.8 years, weight: 69.6 ± 15.2 kg, height: 160.51 ± 5.25 cm) completed an incremental load test until 1RM in the bilateral leg-press exercise. The MV and the PV of the concentric phase were measured in each repetition using a linear velocity transducer, and were analysed by regression models using LA and PA. A very close relationship of MV (R²= 0.924; p < 0.0001; SEE = 0.08m^.s^-1 by LA, and R² = 0.952; p < 0.0001; SEE = 0.063 m^.s^-1 by PA) and PV (R² = 0.928; p < 0.0001; SEE = 0.119 m^.s^-1 by LA and R² = 0.941; p < 0.0001; SEE = 0.108 m^.s^-1 by PA) with %1RM were observed. The MV of 1RM was 0.24 ± 0.03 m·s^-1, whereas the PV at 1RM was 0.60 ± 0.10 m^.s^-1. A comprehensive analysis of the bilateral leg-press load-velocity relationship in breast cancer survivors is presented. The results suggest that MV is the most recommendable velocity variable to prescribe the relative load during resistance training, and that the PA presents better accuracy to predict velocities associated with each %1RM, although LA is sufficiently valid to use this model as an alternative to the quadratic model. The implications for resistance training in breast cancer are discussed.

Cancer outcomes research-a European challenge: measures of the cancer burden

In a mission that aims to improve cancer control throughout Europe, the European Academy of Cancer Sciences has defined two key indicators of progress: within one to two decades, overall cancer-specific 10-year survival should reach 75%, and in each country, overall cancer mortality rates should be convincingly declining. To lay the ground for assessment of progress and to promote cancer outcomes research in general, we have reviewed the most common population-based measures of the cancer burden. We emphasize the complexities and complementary approaches to measure cancer survival and the novel opportunities for improved assessment of quality of life. We propose that: incidence and mortality rates are standardized to the European population; net survival is used as the measure of prognosis but with proper adjustments for confounding when temporal trends in overall cancer survival are assessed; and cancer-specific quality of life is measured by a combination of existing questionnaires and utilizes emerging communication technologies. We conclude that all measures are important and that a meaningful interpretation also requires a deep understanding of the larger clinical and public health context.