Cancer Biology

Eliminating Aggressive Cancers via PROTAC-like Inducers of Ferroptosis

1. Avital Oknin-Vaisman
2. Deepanjan Panda
3. Rostislav Novak
4. Eliya Bitman-Lotan
5. Nikolett Pahor
6. Yamen Abu Ahmed
7. Guy Kamnesky
8. Markus E. Diefenbacher
9. Ashraf Brik
10. Amir Orian

Reviewed by Arcadia Science

Metastatic small cell lung cancer arises from TP53/RB1-deficient and MYC overproduction hESC-derived PNECs

1. Huanhuan Joyce Chen
2. Eric E Gardner
3. Yajas Shah
4. Kui Zhang
5. Abhimanyu Thakur
6. Chen Zhang
7. Olivier Elemento
8. Harold Varmus

• Curated by eLife

  eLife Assessment

  Given a great need for novel human model systems to study small cell lung cancer (SCLC), the authors describe an important pre-clinical model with broad potential for the study of how genetic perturbations or drug treatments alter SCLC tumor growth, metastasis, and response to therapy. For the major finding, the authors provide convincing evidence that RB/TP53 suppression coupled with MYC overexpression in an ES cell-derived model system results in aggressive and metastatic SCLC. However, the impact of the work would have been increased with the inclusion of a broader set of genetic perturbations, such as over-expression of MYCL, to better model major SCLC phenotypes. The new model described will be of significant interest to researchers studying lung cancer.

Reviewed by eLife

Single-cell profiling reveals the intratumor heterogeneity and immunosuppressive microenvironment in cervical adenocarcinoma

1. Yang Peng
2. Jing Yang
3. Jixing Ao
4. Yilin Li
5. Jia Shen
6. Xiang He
7. Dihong Tang
8. Chaonan Chu
9. Congrong Liu
10. Liang Weng

• Curated by eLife

  eLife Assessment

  In this useful manuscript, the authors performed scRNA-seq on a diverse cohort of 15 early-stage cervical cancer patients. Correlative data is provided to support the possible establishment of an immunosuppressive microenvironment near SCL26A3+ cells, and an association of these cells with upstaging at time of surgery. However without more extensive validation, the evidence supporting the conclusions remains incomplete. Overall, this paper will provide a potentially helpful dataset for researchers studying cervical cancer.

Reviewed by eLife

Targeting the Hippo pathway in cancers via ubiquitination dependent TEAD degradation

1. Trang H Pham
2. Kanika Bajaj Pahuja
3. Thijs J Hagenbeek
4. Jason Zbieg
5. Cameron L Noland
6. Victoria C Pham
7. Xiaosai Yao
8. Christopher M Rose
9. Kristen C Browder
10. Ho-June Lee
11. Mamie Yu
12. May Liang-Chu
13. Scott Martin
14. Erik Verschueren
15. Jason Li
16. Marta H Kubala
17. Rina Fong
18. Maria Lorenzo
19. Paul Beroza
20. Peter Hsu
21. Sayantanee Paul
22. Elisia Villemure
23. Wendy Lee
24. Tommy K Cheung
25. Saundra Clausen
26. Jennifer Lacap
27. Yuxin Liang
28. Jason Cheng
29. Steve Schmidt
30. Zora Modrusan
31. Michael Cohen
32. James Crawford
33. Heinrich Jasper
34. Alan Ashworth
35. Jennie R Lill
36. Shiva Malek
37. Joachim Rudolph
38. Ingrid E Wertz
39. Matthew T Chang
40. Xin Ye
41. Anwesha Dey

• Curated by eLife

  eLife Assessment

  This important study describes two findings: first, that TEAD is subject to turnover by the ubiquitin-proteasome system involving RNF146 and Parylation, and second, the development of a pan-TEAD heterobifunctional degrader that is used to inhibit growth of a YAP-dependent cancer cell line and to characterize TEAD binding sites in the genome. Convincing evidence supports the development and specificity of the degrader. This article will be of relevance to cancer biologists and scientists interested in proteostasis, cellular signaling, and post-translation modification of proteins.

Reviewed by eLife

Establishing the foundations for a data-centric AI approach for virtual drug screening through a systematic assessment of the properties of chemical data

1. Allen Chong
2. Ser-Xian Phua
3. Yunzhi Xiao
4. Woon Yee Ng
5. Hoi Yeung Li
6. Wilson Wen Bin Goh

• Curated by eLife

  eLife Assessment

  This study reports valuable findings that highlight the importance of data quality and data representation for ligand-based virtual screening experiments. The authors' claims are supported by solid evidence, although the conclusions have been inferred from only two datasets. The work would gain much impact if additional datasets were used. The main findings will be of interest to cheminformaticians and medicinal chemists working in QSAR modeling, and possibly in other areas related to machine learning.

Reviewed by eLife

Finding novel vulnerabilities of hypomorphic BRCA1 alleles

1. Anne Schreuder
2. Klaas de Lint
3. Mariana M. Góis
4. Rosalie A. Kampen
5. Marta San Martin Alonso
6. Ilse Nootenboom
7. Veronica Garzero
8. Rob M. F. Wolthuis
9. Sylvie M. Noordermeer

Reviewed by Review Commons

Stochastic variation in the FOXM1 transcription program mediates replication stress tolerance

1. Hendrika A. Segeren
2. Kathryn A. Wierenga
3. Frank M. Riemers
4. Elsbeth A. van Liere
5. Bart Westendorp

Reviewed by Review Commons

Atypical contribution of caspase-3 to melanoma cancer cell motility by regulation of coronin 1B activity

1. Kevin Berthenet
2. Serena Diazzi
3. Catherine Jamard
4. Kinga Stopa
5. Stefan Dragan
6. Deborah Fanfone
7. Trang Nguyen
8. Nathalie Al
9. Francois Virard
10. Olivier Meurette
11. Nikolay Popgeorgiev
12. Hector Hernandez-Vargas
13. Julien Ablain
14. Gabriel Ichim

Reviewed by Review Commons

StereoSiTE: a framework to spatially and quantitatively profile the cellular neighborhood organized iTME

1. Xing Liu
2. Chi Qu
3. Chuandong Liu
4. Na Zhu
5. Huaqiang Huang
6. Fei Teng
7. Caili Huang
8. Bingying Luo
9. Xuanzhu Liu
10. Min Xie
11. Feng Xi
12. Mei Li
13. Liang Wu
14. Yuxiang Li
15. Ao Chen
16. Xun Xu
17. Sha Liao
18. Jiajun Zhang

Reviewed by GigaScience

Unveiling chemotherapy-induced immune landscape remodeling and metabolic reprogramming in lung adenocarcinoma by scRNA-sequencing

1. Yiwei Huang
2. Gujie Wu
3. Guoshu Bi
4. Lin Cheng
5. Jiaqi Liang
6. Ming Li
7. Huan Zhang
8. Guangyao Shan
9. Zhengyang Hu
10. Zhencong Chen
11. Zongwu Lin
12. Wei Jiang
13. Qun Wang
14. Junjie Xi
15. Shanye Yin
16. Cheng Zhan

• Curated by eLife

  eLife Assessment

  This study reports single-cell RNA sequencing results of lung adenocarcinoma, comparing 4 treatment-naive and 5 post-neoadjuvant chemotherapy tumor samples. Of interest is the delineation of two macrophage subtypes: Anti-mac cells (CD45+CD11b+CD86+) and Pro-mac cells (CD45+CD11b+ARG+), with the proportion of Pro-mac/pro-tumorigenic cells significantly increasing in LUAD tissues after neoadjuvant chemotherapy. In terms of significance, the findings might be useful. However issues remain after the revision with lengthy descriptive clustering type analysis, insufficient statistical support, and inefficient figure presentation. As it stands, the level of supportive evidence is inadequate.

Reviewed by eLife