Interviews with Outstanding Authors (2024)

In 2024, many authors make outstanding contributions to our journal. Their articles published with us have received very well feedback in the field and stimulate a lot of discussions and new insights among the peers.

Hereby, we would like to highlight some of our outstanding authors who have been making immense efforts in their research fields, with a brief interview of their unique perspectives and insightful views as authors.

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Reviewer of the Month (2024)

In 2024, TCR reviewers continue to make outstanding contributions to the peer review process. They demonstrated professional effort and enthusiasm in their reviews and provided comments that genuinely help the authors to enhance their work.

Hereby, we would like to highlight some of our outstanding reviewers, with a brief interview of their thoughts and insights as a reviewer. Allow us to express our heartfelt gratitude for their tremendous effort and valuable contributions to the scientific process.

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TCR 2023 Annual Report

Greetings from the Editorial Office of TCR!

We are pleased to share the 2023 Annual Report of Translational Cancer Research. 2023 has seen much progress for TCR. We hope 2023 will bring greater things to TCR. We would like to thank you for your support and assistance in improving the journal over the past year, and we certainly look forward to your innovations and contributions in 2024.

We would especially like to express our sincere gratitude to the editorial board members, guest editors, reviewers, authors, and readers for all your support and contributions to TCR. We wish you a happy, healthy and prosperous 2024!

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New Impact Factor for Translational Cancer Research: 0.9

We are pleased to announce that Translational Cancer Research (TCR) has attained its latest impact factor update for the 2022 citation year: 0.9.

We strive to follow the best practices in publishing. The release of the journal’s latest impact factor is not only a significant achievement for the journal but also the recognition of its more significant scientific reach.

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Translational Cancer Research 2022 CiteScore Released: 1.2

We are pleased to announce that the Translational Cancer Research (TCR) has received its 2022 CiteScore: 1.2, ranking 232 out of 312 journals in the Radiology, Nuclear Medicine and Imaging category.

Furthermore, we are delighted to highlight the remarkable achievements made by all AME journals in the CiteScore ranking.

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Ferroptosis and cuproptosis prognostic signature for prediction of prognosis, immunotherapy and drug sensitivity in hepatocellular carcinoma: development and validation based on TCGA and ICGC databases

Identification of differentially expressed genes. (A) Heatmap revealed differentially expressed genes; (B) univariate Cox regression analysis; (C) a protein-protein interaction network showing the relationship between ferroptosis-related genes and cuproptosis-related genes.

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Bartholin’s gland carcinoma—the diagnostic and management challenges of a rare malignancy—a case report and review of current literature

FDG-avid right inguinal lymph node on axial CT-PET. The green arrow: FDG-avid right inguinal lymph node on axial CT-PET. FDG, fluorodeoxyglucose; CT-PET, computed tomography-positron-emission tomography.

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Development of a novel angiogenesis-related lncRNA signature to predict the prognosis and immunotherapy of glioblastoma multiforme

Differences in risk scores for clinical characteristics. (A-D) The correlations between the risk score and sex, age, MGMT status, and IDH1 status were not significant (P>0.05). (E) Among the subtypes, the proneural subtypes had a significantly lower risk score than did the mesenchymal subtypes (P<0.05). **, P<0.01. IDH1, isocitrate dehydrogenase 1; MGMT, O6-methylguanine-DNA methyltransferase; ns, no significance.

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Integrated analysis of single-cell and bulk transcriptome identifies a signature based on NK cell marker genes to predict prognosis and therapeutic response in clear cell renal cell carcinoma

Single-cell sequencing analysis of 20,074 cells from 7 ccRCC samples. (A) Pearson’s correlation between nFeature and nCount. (B) PCA plot colored by different samples. (C) Cells were classified into 25 clusters via UMAP algorithm. (D) Eight cell types were identified and annotated by marker genes. (E) Heatmap visualized top 5 marker genes among 8 cell clusters. (F) Visualization of gene expression in cell clusters. PC, principal component; UMAP, uniform manifold approximation and projection; NK, nature killer; ccRCC, clear cell renal cell carcinoma; PCA, principal component analysis.

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Development and validation of nomograms to predict early death in non-small cell lung cancer patients with brain metastasis: a retrospective study in the SEER database

ROC curves for the nomograms of the all-cause early death and the cancer-specific early death in the training cohort (A,B) as well as in the validation cohort (C,D). ROC, receiver operating characteristic; AUC, area under the curve.

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