Science Explorer Interactive view Map

Cancer therapeutics and mechanisms

Cancer therapeutics and mechanisms is a research topic within Molecular Biology. Science Explorer counts 35k research works in it since 1950. 14.8% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the structure, function, inhibition, and genetic variants of DNA topoisomerases, particularly their roles in chemotherapy, the mechanism of action of specific inhibitors such as irinotecan and quinolones, and their impact on genomic stability. The papers also explore the potential use of genetic variants in predicting drug toxicity and treatment outcomes.

  • Topoisomerases
  • DNA
  • Inhibitors
  • Chemotherapy
  • Genetic Variants
  • Irinotecan
  • Quinolones
  • Anticancer Drugs
  • Enzyme Mechanism
  • Genomic Stability
Research works
35k
fractional, since 1950
In the world top 10%
5.2k
per year above
Top-10% rate
14.8%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+2%
the tick is no change

Which countries lead Cancer therapeutics and mechanisms research?

By volume, China and the United States publish the most (798 and 680 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 798 works
  2. 2 United States 680 works
  3. 3 India 489 works
  4. 4 Japan 130 works
  5. 5 Egypt 129 works
  6. 6 United Kingdom 97 works
  7. 7 Germany 95 works
  8. 8 Italy 95 works
  9. 9 Russia 94 works
  10. 10 Saudi Arabia 91 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

China: 29.6%United States: 25.2%India: 18.1%Japan: 4.8%6 others listed: 22.3%30%largest
China798 · 29.6%United States680 · 25.2%India489 · 18.1%Japan130 · 4.8%6 others listed602 · 22.3%

Shares of the rows listed above, not of the whole node.

Which institutions lead Cancer therapeutics and mechanisms research?

By volume in 2022–2025, King Saud University publishes the most Cancer therapeutics and mechanisms research, followed by Chinese Academy of Medical Sciences & Peking Union Medical College and Shenyang Pharmaceutical University.

Who are the leading researchers in Cancer therapeutics and mechanisms?

The most-cited researchers publishing on Cancer therapeutics and mechanisms include Hagop M. Kantarjian, Susan G. Arbuck and A. Rosowsky.

  1. 1 Hagop M. Kantarjian United States 4k citations
  2. 2 Susan G. Arbuck United States 3.5k citations
  3. 3 A. Rosowsky Switzerland 3.5k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

Where is Cancer therapeutics and mechanisms research done?

The largest centres of Cancer therapeutics and mechanisms research in 2022–2025 are Beijing (China), Shanghai (China), Guangzhou (China) and Moscow (Russia). Among places with at least 20 works in it, it is an unusually large share of all research in Bethesda, Giza and Hyderabad.

Largest cities, 2022–2025

  1. 1 Beijing China 99 works
  2. 2 Shanghai China 64 works
  3. 3 Guangzhou China 57 works
  4. 4 Moscow Russia 46 works
  5. 5 Cairo Egypt 43 works
  6. 6 New York United States 41 works
  7. 7 Riyadh Saudi Arabia 38 works
  8. 8 Seoul South Korea 36 works
  9. 9 Hangzhou China 36 works
  10. 10 Nanjing China 34 works

Where it is the local speciality

  1. BethesdaUS · 28.9 works6.5×
  2. GizaEG · 26.0 works4.8×
  3. HyderabadIN · 32.6 works4.8×
← less than its size predictsmore →

Location quotient: how much more of its research is in Cancer therapeutics and mechanisms than the world average.

See Cancer therapeutics and mechanisms on the map

Where is the best place to study Cancer therapeutics and mechanisms?

Among universities, judged by research, Al-Azhar University, King Saud University and Academy of Scientific and Innovative Research score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 21.5%fractional works in this node (log) →share in the world top 10% →Al-Azhar University: 13, 41.4%King Saud University: 21, 26.1%Academy of Scientific and Innovative Research: 12, 20.0%Cairo University: 15, 36.0%Shenyang Pharmaceutical University: 16, 15.1%China Pharmaceutical University: 12, 23.4%Vellore Institute of Technology University: 12, 17.7%Chinese Academy of Medical Sciences & Peking Union Medical College: 19, 14.2%GITAM University: 8, 2.8%Mansoura University: 9, 18.3%Al-Azhar UniversityCairo UniversityKing Saud UniversityAcademy of Scientifi…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Al-Azhar UniversityEgypt 78.941.4%9.2×13 +158.8%
2 King Saud UniversitySaudi Arabia 63.726.1%6.3×21 +6.0%
3 Academy of Scientific and Innovative ResearchIndia 61.520.0%10.4×12 +460.0%
4 Cairo UniversityEgypt 57.736.0%5.2×15 +54.0%
5 Shenyang Pharmaceutical UniversityChina 50.215.1%34.9×16 -15.4%
6 China Pharmaceutical UniversityChina 48.523.4%15.0×12 -28.9%
7 Vellore Institute of Technology UniversityIndia 41.017.7%3.2×12 +246.1%
8 Chinese Academy of Medical Sciences & Peking Union Medical CollegeChina 40.914.2%5.4×19 -19.3%
9 GITAM UniversityIndia 37.32.8%10.2×8 +139.0%
10 Mansoura UniversityEgypt 33.118.3%5.6×9 -16.5%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Cancer therapeutics and mechanisms research growing?

Output in 2018–2022 was 2% higher than in 2013–2017, peaking in 2022. The fastest-growing topics are Cancer therapeutics and mechanisms.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.