Feasibility of online managing cancer and living meaningfully (CALM) in Chinese patients with metastatic breast cancer: a pilot randomized control trial

Metastatic breast cancer could cause various psychological symptoms. Managing Cancer and Living Meaningfully (CALM) is a brief, manualized psychotherapy that has been validated for advanced cancer patients. We conducted a pilot randomized control trial (RCT) to verify the feasibility and preliminary efficacy of CALM therapy in this population. Patients who met the inclusion criteria were randomly assigned into CALM or Wait-list Control (WLC) groups. Patients in the CALM group received CALM therapy and usual care; patients in WLC group first received usual care and then underwent CALM therapy after completing all assessments. All patients were asked to complete three assessments: T0(baseline), T1(3 months), and T2(6 months). The primary outcomes was death anxiety; other outcomes were depression, distress, suicide ideation, attachment security, spiritual well-being and quality of life at the end of life. Analysis of Covariance (ANCOVA) and t-test were used for statistics analysis. Thirty-six patients were randomly assigned to either of the two groups, with 34 patients completing the three assessments. At six months, we found significant between group differences in suicide ideation, distress, and life completion between the CALM and WLC groups. At T2, patients in CALM group reported lower levels of depression (F = 5.016, p = 0.033, partial η2 = 0.143), distress (F = 7.969, p = 0.010, partial η2 = 0.257), attachment avoidance (F = 4.407, p = 0.044, partial η2 = 0.128), and better sense of life completion (F = 5.493, p = 0.026, partial η2 = 0.155) than patients in the WLC group. Compared with results of the T0 assessments, we found significant differences in socres for depression (T2&T0, t = - 2.689, p = 0.011, Cohen's d = 0.940) and distress (T2&T0, t = - 2.453, p = 0.022, Cohen's d = 0.965) between the two groups. CALM therapy was well received by the study population, and CALM therapy can reduce depression, distress, attachment avoidance while improving quality of life in Chinese metastatic breast cancer patients. A Phase III RCT was recommended to verify the impact of CALM therapy on psychological burden and survival in this population.Trial registration: This study is part of the "Preliminary application study for Managing Cancer and Living Meaningfully (CALM) therapy in Chinese advanced cancer patients" clinical trial, with the Trial Registration Number of ChiCTR1900023129 (13/05/2019) in the Chinese Clinical Trial Registry (ChiCTR) website. ( https://www.chictr.org.cn/index.html ).

Natural killer cell-based signature: Prognostic analysis in head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSC) is a challenging cancer with significant clinical implications. Natural killer (NK) cells have emerged as important players in tumor immunosurveillance, yet their role and potential as prognostic biomarkers in HNSC remain unclear.

METHODS

Quantitative analysis using multiple algorithms identified FCRL1, KIR3DL2 and ZNF541 as molecules significantly associated with local NK cell infiltration and patient survival. A prognostic model based on these molecules demonstrated robust predictive performance.

RESULTS

Analysis of high- and low-risk patient groups revealed distinct differences in the tumor microenvironment, indicating an inhibitory immune microenvironment in high-risk patients. Notably, low-risk patients exhibited potential sensitivity to immunotherapy and showed favorable responses to specific drugs such as axitinib, methotrexate, rapamycin and vorinostat. NK cells, important effectors of the innate immune response, were found to play a crucial role in HNSC immunity. The present study provides valuable insights into the correlation between FCRL1, KIR3DL2, ZNF541 and NK cell infiltration, paving the way for future investigations into their roles in HNSC. Activation of NOTCH signaling, MYC targets, DNA repair, E2F targets, epithelial-mesenchymal transition, G2M checkpoint and mitotic spindle pathways in high-risk patients suggests their involvement in disease progression and poor prognosis.

CONCLUSIONS

The present study reveals the significance of NK cells in HNSC and their potential as prognostic biomarkers. The CFKZ score offers a promising approach for predicting patient outcomes and guiding personalized treatment decisions in HNSC. These findings contribute to our understanding of HNSC immunobiology and hold implications for precision medicine in HNSC management.

Lung cancer distress: screening thermometer meta-analysis

OBJECTIVES

The distress is associated with the life quality and prognosis of patients with lung cancer. Distress thermometer (DT) has been widely recommended for distress screening. This study was conducted to summarise the positive rate of distress in patients with lung cancer using DT screenings.

METHODS

The PubMed, Embase, PsyclNFO and Cochrane Library databases were comprehensively searched to identify all eligible studies published before 31 December 2021. Studies were eligible if they were published in peer-reviewed literature and evaluated distress levels by DT.

RESULTS

Ten eligible studies, including a total of 2111 patients, were included in this analysis, and their methodological quality was moderate. The pooled positive rate of distress in patients with lung cancer was 49.04% (95% CI 41.51% to 56.60%). The subgroup analysis revealed that the distress positive rate was significantly different (p<0.05) across North America, Europe and China with values of 53.33% (95% CI 45.22% to 61.37%), 43.81% (95% CI 31.57% to 56.43%) and 38.57% (95% CI 33.89% to 43.41%), respectively. Moreover, the distress positive rate was significantly different between men and women (p<0.05). Additionally, in terms of histological type, clinical tumour, node, metastasis stage, previous treatment and DT threshold, the distress positive rate had no significant differences. No significant publication bias was identified by Begg's funnel plot and Egger's test.

CONCLUSIONS

The summarised distress positive rate was high and was significantly different according to gender and region. DT screening should be recommended for routine clinical practice and more attention should be given towards distress management.

CT-based quantification of trachea shape to detect invasion by thyroid cancer

OBJECTIVE

This study aims to develop a CT-based method for quantifying tracheal shape and evaluating its ability to distinguish between cases with or without tracheal invasion in patients with thyroid carcinoma.

METHODS

A total of 116 quantitative shape features, including 56 geometric moments and 60 bounding shape features, were defined. The tracheal lumen was semi-automatically defined with a CT threshold of less than - 500 HU. Three contiguous slices with the 1st, 2nd, and 3rd smallest trachea lumen areas were contiguously selected, and the appropriate number of slices to be included was determined. Fifty-six patients with differentiated thyroid carcinoma (DTC) invading the trachea and 22 patients with DTC but without invasion were retrospectively included. A receiver operating characteristic (ROC) curve was applied to select the representative shape features and determine the optimal threshold.

RESULTS

23.3%, 25.9%, and 24.1% of the features displayed an area under the ROC curve (AUC) ≥ 0.800 when derived from 1, 2, and 3 slices, respectively. Calculating feature values from two slices with the 1st and 2nd smallest tracheal lumen area were considered appropriate. Six final features, including 3 geometric moments and 3 bounding shape features, were selected to determine the tracheal invasion status of DTC and displayed AUCs of 0.875-0.918, accuracies of 0.821-0.891, sensitivities of 0.813-0.893, and specificities of 0.818-0.932, outperforming the visual evaluation results.

CONCLUSIONS

Geometric moments and bounding shape features can quantify the tracheal shape and are reliable for identifying DTC tracheal invasion. The selected features quantified the extent of tracheal deformity in DTC patients with and without tracheal invasion.

CLINICAL RELEVANCE STATEMENT

Six geometric features provide a non-invasive, semi-automated evaluation of the tracheal invasion status of thyroid cancer.

KEY POINTS

• A novel method for quantifying tracheal shape using 56 geometric moments and 60 bounding shape features was developed. • Six features identify tracheal invasion by thyroid carcinoma. • The selected features quantified the extent of tracheal deformity in differentiated thyroid carcinoma patients with and without tracheal invasion.

Infiltrating myeloid cell diversity determines oncological characteristics and clinical outcomes in breast cancer

BACKGROUND

Breast cancer presents as one of the top health threats to women around the world. Myeloid cells are the most abundant cells and the major immune coordinator in breast cancer tumor microenvironment (TME), target therapies that harness the anti-tumor potential of myeloid cells are currently being evaluated in clinical trials. However, the landscape and dynamic transition of myeloid cells in breast cancer TME are still largely unknown.

METHODS

Myeloid cells were characterized in the single-cell data and extracted with a deconvolution algorithm to be assessed in bulk-sequencing data. We used the Shannon index to describe the diversity of infiltrating myeloid cells. A 5-gene surrogate scoring system was then constructed and evaluated to infer the myeloid cell diversity in a clinically feasible manner.

RESULTS

We dissected the breast cancer infiltrating myeloid cells into 15 subgroups including macrophages, dendritic cells (DCs), and monocytes. Mac_CCL4 had the highest angiogenic activity, Mac_APOE and Mac_CXCL10 were highly active in cytokine secretion, and the DCs had upregulated antigen presentation pathways. The infiltrating myeloid diversity was calculated in the deconvoluted bulk-sequencing data, and we found that higher myeloid diversity was robustly associated with more favorable clinical outcomes, higher neoadjuvant therapy responses, and a higher rate of somatic mutations. We then used machine learning methods to perform feature selection and reduction, which generated a clinical-friendly scoring system consisting of 5 genes (C3, CD27, GFPT2, GMFG, and HLA-DPB1) that could be used to predict clinical outcomes in breast cancer patients.

CONCLUSIONS

Our study explored the heterogeneity and plasticity of breast cancer infiltrating myeloid cells. By using a novel combination of bioinformatic approaches, we proposed the myeloid diversity index as a new prognostic metric and constructed a clinically practical scoring system to guide future patient evaluation and risk stratification.

The molecular mechanism of circRHOBTB3 inhibits the proliferation and invasion of epithelial ovarian cancer by serving as the ceRNA of miR-23a-3p

Rising evidences bespeak that circular RNAs are indispensable in regulating cellular biological behaviors and engaging in diseases' occurrence. CircRHOBTB3 has been reported to participate intimately in the progression of some cancers. Nevertheless, the mechanism by which circRHOBTB3 regulates tumorigenesis in epithelial ovarian cancer (EOC) remains ill-defined. The present study determined the expression pattern and bio-effects of circRHOBTB3 in EOC. Furthermore, it revealed that circRHOBTB3 could serve as the ceRNA of miR‑23a-3p to facilitate PTEN expression, suppress proliferation, G1/S transition, invasion, and promote apoptosis in EOC. Summarily, our findings provided a primary research foundation that circRHOBTB3 might be typified as a neoteric biomarker and a promising target of EOC, which is essential for improving the early diagnosis and precision treatment, so as to cut down EOC's mortality finally.

Comprehensive Characterization of the Genomic Landscape in Chinese Pulmonary Neuroendocrine Tumors Reveals Prognostic and Therapeutic Markers (CSWOG-1901)

BACKGROUND

Pulmonary neuroendocrine tumors (pNETs) include typical carcinoid (TC), atypical carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC), and small cell lung carcinoma (SCLC). The optimal treatment strategy for each subtype remains elusive, partly due to the lack of comprehensive understanding of their molecular features. We aimed to explore differential genomic signatures in pNET subtypes and identify potential prognostic and therapeutic biomarkers.

METHODS

We investigated genomic profiles of 57 LCNECs, 49 SCLCs, 18 TCs, and 24 ACs by sequencing tumor tissues with a 520-gene panel and explored the associations between genomic features and prognosis.

RESULTS

Both LCNEC and SCLC displayed higher mutation rates for TP53, PRKDC, SPTA1, NOTCH1, NOTCH2, and PTPRD than TC and AC. Small cell lung carcinoma harbored more frequent co-alterations in TP53-RB1, alterations in PIK3CA and SOX2, and mutations in HIF-1, VEGF and Notch pathways. Large cell neuroendocrine carcinoma (12.7 mutations/Mb) and SCLC (11.9 mutations/Mb) showed higher tumor mutational burdens than TC (2.4 mutations/Mb) and AC (7.1 mutations/Mb). 26.3% of LCNECs and 20.8% of ACs harbored alterations in classical non-small cell lung cancer driver genes. The presence of alterations in the homologous recombination pathway predicted longer progression-free survival in advanced LCNEC patients with systemic therapy (P = .005) and longer overall survival (OS) in SCLC patients with resection (P = .011). The presence of alterations in VEGF (P = .048) and estrogen (P = .018) signaling pathways both correlated with better OS in patients with resected SCLC.

CONCLUSION

We performed a comprehensive genomic investigation on 4 pNET subtypes in the Chinese population. Our data revealed distinctive genomic signatures in subtypes and provided new insights into the prognostic and therapeutic stratification of pNETs.

A feasibility study on an automated method to generate patient-specific dose distributions for radiotherapy using deep learning

PURPOSE

To develop a method for predicting optimal dose distributions, given the planning image and segmented anatomy, by applying deep learning techniques to a database of previously optimized and approved Intensity-modulated radiation therapy treatment plans.

METHODS

Eighty cases of early-stage nasopharyngeal cancer (NPC) were included in the study. Seventy cases were chosen randomly as the training set and the remaining as the test set. The inputs were the images with structures, with each target and organs at risk (OARs) assigned a unique label. The outputs were dose maps, including coarse dose maps and converted fine dose maps (FDM) from convolution. Two types of input images with structures were used in the model building. One type of input included the images (with associated structures) without manipulation. The second type of input involved modifying the image gray label with information from radiation beam geometry. ResNet101 was chosen as the deep learning network for both. The accuracy of predicted dose distributions was evaluated against the corresponding dose as used in the clinic. A global three-dimensional gamma analysis was calculated for the evaluation.

RESULTS

The proposed model trained with the two different sets of input images and structures could both predict patient-specific dose distributions accurately. For the out-of-field dose distributions, the model obtained from the input with radiation geometry performed better (dose difference in %, 4.7 ± 6.1% vs 5.5 ± 7.9%, P < 0.05). The mean Gamma pass rates of dose distributions predicted with both types of input were comparable for most OARs (P > 0.05), except for the bilateral optic nerves and the optic chiasm.

CONCLUSIONS

The proposed system with radiation geometry added to the input is a promising method to generate patient-specific dose distributions for radiotherapy. It can be applied to obtain the dose distributions slice-by-slice for planning quality assurance and for guiding automated planning.