Lao H. Saal

12.2k total citations · 3 hit papers
76 papers, 7.2k citations indexed

About

Lao H. Saal is a scholar working on Cancer Research, Molecular Biology and Oncology. According to data from OpenAlex, Lao H. Saal has authored 76 papers receiving a total of 7.2k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Cancer Research, 37 papers in Molecular Biology and 25 papers in Oncology. Recurrent topics in Lao H. Saal's work include Cancer Genomics and Diagnostics (28 papers), Breast Cancer Treatment Studies (11 papers) and Cancer Cells and Metastasis (10 papers). Lao H. Saal is often cited by papers focused on Cancer Genomics and Diagnostics (28 papers), Breast Cancer Treatment Studies (11 papers) and Cancer Cells and Metastasis (10 papers). Lao H. Saal collaborates with scholars based in Sweden, United States and Germany. Lao H. Saal's co-authors include Åke Borg, Markus Ringnér, Carsten Peterson, Paul S. Meltzer, Javed Khan, Frank Westermann, Frank Berthold, Marc Ladanyi, Manfred Schwab and Jun S. Wei and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Medicine.

In The Last Decade

Lao H. Saal

73 papers receiving 7.0k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks

2001 1.9k citations Javed Khan, Jun S. Wei et al. Nature Medicine profile →
PIK3CA Mutations Correlate with Hormone Receptors, Node Metastasis, and ERBB2, and Are Mutually Exclusive with PTEN Loss in Human Breast Carcinoma

2005 681 citations Lao H. Saal, Karolina Holm et al. Cancer Research profile →
Estrogen receptor status in breast cancer is associated with remarkably distinct gene expression patterns.

2001 540 citations Markus Ringnér, Lao H. Saal et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Lao H. Saal Sweden	30	4.7k	2.1k	2.0k	1.1k	857	76	7.2k
Anke Witteveen Netherlands	10	5.1k 1.1×	2.7k 1.3×	3.1k 1.5×	869 0.8×	1.0k 1.2×	18	8.1k
Yudong D. He United States	27	6.8k 1.5×	2.8k 1.3×	3.2k 1.6×	828 0.7×	1.3k 1.5×	49	10.6k
Matthew J. Marton United States	18	7.5k 1.6×	2.5k 1.2×	2.8k 1.4×	767 0.7×	1.4k 1.6×	45	10.6k
Craig H. Mermel United States	24	4.5k 0.9×	2.1k 1.0×	3.0k 1.5×	1.8k 1.6×	818 1.0×	31	8.0k
Phillip G. Febbo United States	38	4.8k 1.0×	1.9k 0.9×	2.7k 1.3×	3.3k 3.0×	861 1.0×	114	8.9k
Kyle Ellrott United States	13	4.4k 0.9×	1.2k 0.5×	2.4k 1.2×	935 0.8×	599 0.7×	28	6.2k
Brad Ozenberger United States	2	3.9k 0.8×	1.1k 0.5×	2.2k 1.1×	900 0.8×	605 0.7×	2	5.6k
Kenna Shaw United States	28	4.7k 1.0×	2.3k 1.1×	3.2k 1.6×	1.6k 1.4×	700 0.8×	83	7.9k
Johan Lundin Finland	48	2.6k 0.6×	2.8k 1.3×	1.6k 0.8×	1.0k 0.9×	915 1.1×	160	7.5k
Holly K. Dressman United States	39	4.5k 1.0×	1.4k 0.7×	1.9k 1.0×	716 0.6×	581 0.7×	75	6.7k

Countries citing papers authored by Lao H. Saal

Since Specialization

Citations

This map shows the geographic impact of Lao H. Saal's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lao H. Saal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lao H. Saal more than expected).

Fields of papers citing papers by Lao H. Saal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lao H. Saal. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lao H. Saal. The network helps show where Lao H. Saal may publish in the future.

Co-authorship network of co-authors of Lao H. Saal

This figure shows the co-authorship network connecting the top 25 collaborators of Lao H. Saal. A scholar is included among the top collaborators of Lao H. Saal based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lao H. Saal. Lao H. Saal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Grimm, Christoph, Christian Brueffer, Núria Seguí, et al.. (2025). ctDNA as an Objective Marker for Postoperative Residual Disease in Primary Advanced High-Grade Serous Ovarian Cancer. Cancers. 17(5). 786–786.

Saal, Lao H., Niklas Loman, Yilun Chen, et al.. (2024). Monitoring ctDNA dynamics in early breast cancer using a novel ultra-sensitive tumor-informed structural variant approach combining whole-genome sequencing and multiplex dPCR.. Journal of Clinical Oncology. 42(16_suppl). 568–568. 1 indexed citations

Brueffer, Christian, Miguel Alcaide, Lucia Oton, et al.. (2023). #898 Tumor-informed CtDNA detection as a marker for postoperative residual disease in epithelial ovarian cancer – results of a feasibility study. A38.2–A39. 1 indexed citations

Chen, Yilun, et al.. (2023). Preoperative ctDNA Levels Are Associated With Poor Overall Survival in Patients With Ovarian Cancer. Cancer Genomics & Proteomics. 20(6suppl). 763–770. 8 indexed citations

Demircan, Kamil, Thilo Samson Chillon, Johan Vallon‐Christersson, et al.. (2023). Matched analysis of circulating selenium with the breast cancer selenotranscriptome: a multicentre prospective study. Journal of Translational Medicine. 21(1). 1 indexed citations

Dahlgren, Malin, Anthony M. George, Christian Brueffer, et al.. (2021). Preexisting Somatic Mutations of Estrogen Receptor Alpha (ESR1) in Early-Stage Primary Breast Cancer. JNCI Cancer Spectrum. 5(2). 16 indexed citations

Brueffer, Christian, Christof Winter, Johan Vallon‐Christersson, et al.. (2020). The mutational landscape of the SCAN ‐B real‐world primary breast cancer transcriptome. EMBO Molecular Medicine. 12(10). e12118–e12118. 42 indexed citations

Bendahl, Pär‐Ola, Åke Borg, Anna Ehinger, et al.. (2019). Agreement between molecular subtyping and surrogate subtype classification: a contemporary population-based study of ER-positive/HER2-negative primary breast cancer. Breast Cancer Research and Treatment. 178(2). 459–467. 20 indexed citations

Isaksson, Sofi, Anthony M. George, Mats Jönsson, et al.. (2019). Pre-operative plasma cell-free circulating tumor DNA and serum protein tumor markers as predictors of lung adenocarcinoma recurrence. Acta Oncologica. 58(8). 1079–1086. 19 indexed citations

10.

Johnson, Kristin, Sophia Zackrisson, Aldana Rosso, et al.. (2019). Tumor Characteristics and Molecular Subtypes in Breast Cancer Screening with Digital Breast Tomosynthesis: The Malmö Breast Tomosynthesis Screening Trial. Radiology. 293(2). 273–281. 22 indexed citations

11.

Vallon‐Christersson, Johan, Jari Häkkinen, Cecilia Hegardt, et al.. (2019). Cross comparison and prognostic assessment of breast cancer multigene signatures in a large population-based contemporary clinical series. Scientific Reports. 9(1). 12184–12184. 36 indexed citations

12.

Vallon‐Christersson, Johan, Cecilia Hegardt, Lao H. Saal, et al.. (2019). Prediction of Lymph Node Metastasis in Breast Cancer by Gene Expression and Clinicopathological Models: Development and Validation within a Population-Based Cohort. Clinical Cancer Research. 25(21). 6368–6381. 37 indexed citations

13.

Pappas, Kyrie, Jia Xu, Sakellarios Zairis, et al.. (2017). p53 Maintains Baseline Expression of Multiple Tumor Suppressor Genes. Molecular Cancer Research. 15(8). 1051–1062. 48 indexed citations

14.

Chen, Yilun, Marc J. van de Vijver, Hanina Hibshoosh, Ramon Parsons, & Lao H. Saal. (2015). PTEN and NEDD4 in Human Breast Carcinoma. Pathology & Oncology Research. 22(1). 41–47. 19 indexed citations

15.

Howlin, Jillian, Helena Cirenajwis, Barbara Lettiero, et al.. (2015). Loss of CITED1, an MITF regulator, drives a phenotype switch in vitro and can predict clinical outcome in primary melanoma tumours. PeerJ. 3. e788–e788. 16 indexed citations

16.

Fine, Barry, Cindy Hodakoski, Susan Koujak, et al.. (2009). Activation of the PI3K Pathway in Cancer Through Inhibition of PTEN by Exchange Factor P-REX2a. Science. 325(5945). 1261–1265. 182 indexed citations

17.

Gruvberger-Saal, Sofia K., Pär‐Ola Bendahl, Lao H. Saal, et al.. (2007). Estrogen Receptor β Expression Is Associated with Tamoxifen Response in ERα-Negative Breast Carcinoma. Clinical Cancer Research. 13(7). 1987–1994. 154 indexed citations

18.

Saal, Lao H., Karolina Holm, Matthew Maurer, et al.. (2005). PIK3CA Mutations Correlate with Hormone Receptors, Node Metastasis, and ERBB2, and Are Mutually Exclusive with PTEN Loss in Human Breast Carcinoma. Cancer Research. 65(7). 2554–2559. 681 indexed citations breakdown →

19.

Khan, Javed, Lao H. Saal, Michael Bittner, et al.. (2003). Gene Expression Profiling in Cancer Using cDNA Microarrays. Humana Press eBooks. 68. 205–222. 9 indexed citations

20.

Khan, Javed, Jun S. Wei, Markus Ringnér, et al.. (2001). Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nature Medicine. 7(6). 673–679. 1919 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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